Eric Kavanagh: Ladies and gentleman, hello and welcome back once again to TechWise. My name is Eric Kavanagh. I will be your moderator for Episode 3. This is a new show that we have designed with our friends from Techopedia, a very cool website that obviously focuses on technology, and of course, here at The Bloor Group, we focus quite keenly on enterprise technology. So, enterprise software of all kinds, and the whole TechWise format was designed to give our attendees a real good hard look at a specific space. So, we have done Hadoop for example, we did analytics in the last show and in this particular show, we are talking all about cloud.

So, it's called "The Cloud Imperative - What, Where, When and How." We are gonna talk with a couple of analysts today and then three vendors. So, Qubole, Cloudant and Attunity are the sponsors of today's show. A big thank you for those folks for their time and attention today and a big thanks, of course, to all of you out there. And keep in mind that as attendees of these shows, you play a significant role. We want you to ask questions, get involved, get interactive, let us know what you think because obviously, the whole purpose of the show here is to help you guys understand what's happening out there in the world of cloud computing.



So, let's move right along. First host, your host up there, Eric Kavanagh that's me and then we have Dr. Robin Bloor calling in from an airport, as a matter of fact and our good friend Gilbert, Gilbert Van Cutsem, an independent analyst, is also gonna be sharing some thoughts with you. Then we will hear from Ashish Thusoo, CEO and co-founder of Qubole. We will hear from Mike Miller, chief scientist at Cloudant and finally from Lawrence Schwartz, VP of Marketing at Attunity. So, we got a whole lot of content lined up for you today.

So, the cloud — edict from above — this is a concept that came to me the other day when I was thinking about this. Really, cloud computing is just huge these days. I mean, it's really quite fascinating to watch the evolution of this stuff and one of the examples I often give is in the webcasting technology itself. Of course, those of you who dialed in early heard some interesting technical challenges. That is one problem with the cloud is it does change, formats change, standards change, interfaces change and sometimes when you try to hook up two different areas together, you get some difficulty, you get some trouble. So, this is actually one of the things to worry about with cloud computing. Be careful about architecture! You can see that at the last bullet point.

One of the things that we do, just as a side note here, for our webcast, we have a separate phone conferencing vendor. Then we use WebEx. We do not use the WebEx audio because frankly, one time we used WebEx audio years ago and it crashed and burned in a most unpleasant way. Thus, we are not willing to run that risk again. So, we use our own audio recording company called Arkadin as a matter of fact and we stitch together, in real time, all these different solutions. And the idea is that we could then email you with a separate email application with the slides in case for example, WebEx would have crashed, we tell you all to dial in, we'd email you the slides and just go through it more or less without the WebEx kind of environments. So, the way that you can get around these kinds of problems, but these kinds of issues are all over the place.

But, there are lots of benefits to cloud. Obviously, it's a low barrier to entry, you can look at the poster child of cloud computing is salesforce.com of course, which just revolutionized business, specifically sales force automation, obviously. But, then you have got stuff like Marketo and iContact and Constant Contact and Sailthru and, goodness gracious, in terms of marketing and sales automation, there are tons of tools, but that's not all there is. HR is getting it to the whole cloud game, analytics is in the cloud game. Look at that little-known company out there Amazon Web Services, what they are doing with cloud computing — it's just massive. And I heard a great quote the other day from a guy we do a lot of work with David [Bessamer(?)] who now is over at Cisco, as a matter of fact, the company that bought WebEx. Not sure they have invested as much as I would like them to have in WebEx, but that's not really my decision, is it? But, he is at Cisco these days and he had a very funny, just pithy quote, and that is, "there is not one cloud, there are many clouds," and that's exactly right. There are lots and lots of clouds out there. In fact, every cloud provider is its own cloud. So, one of the challenges these days is to connect cloud, right? If you are sales force, wouldn't it be nice to connect directly to iContact and the Constant Contact and to LinkedIn, for example, and maybe to Twitter and other environments, other clouds out there just fixed together business solutions that make sense for you and your company.

So, these are some issues to keep in mind, but cloud is here to stay. Just know that about that, on-premise software is here to stay. So, what we have to figure out in the enterprise or any even small- to mid-sized businesses, how do you define your architecture and maintain it such that you can leverage cloud without creating a giant [silo(?)] up somewhere else outside of your control? So, obviously the whole data warehousing industry evolved around a need to consolidate critical information in order to analyze that information and make better decisions.

Well, now Amazon Web Services has Redshift. That's one of the biggest webcasts we ever did was with Redshift. That's a pretty big deal. They are changing the dynamics, they are changing the pricing structures. You can watch as your pricing goes down on traditional enterprise software licensing in part because of cloud computing and part because these folks are out there lowering the price point, putting pressure on price. So, that's good news for the end users. It's something to keep in mind certainly for anyone out there who is trying to use some of these technologies. So, it's something to keep in mind and we will talk about that today on the show.

So, analyst Dr. Robin Bloor is gonna be our first analyst for the day. So, I will go ahead and push his first slide and hand the keys over to him. Robin, I think you’re in here somewhere, there you are. And with that I’m going to hand it off, and the floor is yours!

Dr. Robin Bloor: Okay, Eric. Thanks for that introduction. I came across… a couple of days ago, I came across a survey of consumers, in actual fact, which asked the question — do you think that stormy weather interferes with cloud computing? And more than 50 percent of them said yes. I just thought I’d let you know that it doesn't, if you’re one of those believing in that. And then, that's a bit like believing that, you know, when you’ve got snow on the television is because it's snowing outside.

Cloud, you know, one of the things is it's kind of, you know, an important, if you like, simple detail of the cloud is that the cloud is actually a data center in one way or another, or any particular cloud service is a data center. The only thing is, it's a different data center than the traditional cloud. So, I was gonna talk in overview about the cloud so that as your backup to go into more detail about cloud usage because no point in covering the same ground.

So, the first kind of point that I would like to make is that cloud's a service, you know? And one of the things that's actually happening because of cloud computing is that there's a... well, I call the death of brands, a whole series of software brands had an awful lot of power and continue to have powers in corporate computing. Once you get to the cloud, they don't have much power anymore, you know? When you buy a cloud service, you care about the application, of course, you care about the service level the cloud’s going to give you, you don’t want the cloud service failing frequently, you care about usage cost and you care about these things because this is a service, but what you don't care about anymore is that you don't care what hardware it’s running on particularly, you don't care what the networking technology is, you don't care what the operating system it’s running is, you don't care what the file systems are, you don't even care what the database is and that's actually used specifically by any given database services out of the cloud, you know? And the impact of that in a way is that the cloud is an awful lot of software brands have no real value in the cloud because, you know, you go into the cloud in one way or another for something that’s a service and not anymore a product. So, I thought I could do a couple of slides of reasons not to use the cloud, you know, and these are all, if you like, you know, bloody simple, obvious reasons, but somebody had to state them, so, I thought I would.

So, reasons not to me... not to use the cloud — if they can’t provide the kind of data and process governance you want them, you know, then it simply doesn't meet your criteria. If they can't give you the performance that you want, it's not going to meet the criteria. If the cloud gives you the flexibility in terms of how you can move stuff around then it's not gonna meet a criteria. That's just obvious reasons why particular cloud services wouldn't suit an awful lot of people out there other than doing corporate computing.

You might not do it because you can do it cheaper. The cloud isn't always the cheapest option. Some people seem to think because it's often an inexpensive option it's always gonna be cheaper, it isn't always cheaper. And the other thing is that if you are taking an application from a cloud, it doesn't integrate well with what you are doing, then you are probably not going to go forward with it and those are, you know, reasons to turn away.

Here are the reasons to adopt. You know, one of the things you can do in the cloud, pretty much bulletproof, is prototyping activity. If you either you can prototype in the cloud and implement in the data center, it's entirely viable and there are vast amounts of people doing that. You can upload work from the data center with non-critical applications because they will probably, you would be able to find some kind of cloud services that will meet your service level to the uncritical stuff. And you can upload specific applications like salesforce.com and similar offerings to that, you know, the standard applications. Everybody kind of has a capability in that area and the field isn't specialized and, you know, the traditional... whatever is available in the cloud is probably gonna be what you go with.

So, the final thing that I wanted to say, it's a kinda interesting thing, really, is when you actually look for the cloud, one way of understanding is just as a series of economies of scale. The whole point is that, you know, running a data center out there and you are going to dial in to that data center from somewhere or another and use it and therefore, it would be better, it better be in the main cheaper than if you do it yourself. So, you know, it's really all about economies of scale.

The cloud providers, they choose the data center location and the best place to locate the data center is right next to a power station, and especially right next to an inexpensive power station. So, one power station up north that happens to be hydroelectric or something like that. It's normally the cheapest, you know? You can actually locate the data center there and you will find it’s easier. It's less expensive to hire people in such locations than it is in the center of New York or San Francisco. You can standardize on the whole facility in terms of air conditioning and power. That will save you a lot because it means, you know, you can give out a whole building to it and that's what exactly all the cloud operators do. They standardize on networking hardware, they standardize on the computer hardware they use, normally commodity x86 boards, often they will assemble them themselves. So, some are even actually building the whole thing up. They will use Amazon software that they can because it actually means no cost to adopting it. They will standardize in all software. So, they will never upgrade anything except to upgrade all at once. They will organize the support. So, they will be paying support to multitude of different providers that just have their own support facility. They’ll, have scale-up and scale-out capability in the sense that they will be running more than you would ever be running that kind of service and they will monitor their usage in a way that most data centers can't because they are kind of running only one standardized service, but most data centers are running a whole series of things. And that's what the cloud is all about, really, and that in a certain way, can define whether it interests you or whether it doesn't for any particular application. So, you know, my kind of rough rule of thumb is that where economies of scale are possible, the cloud's gonna take over sooner or later. But, the way innovation and flexibility and a very specific things that you go yourself really can't. The cloud's always gonna be second best.

Okay. Let me pass it back to Eric, or on to Gilbert.

Eric Kavanagh: Okay, Gilbert, I'll give you the keys here to the WebEx. Standby. Just click anywhere on that slide and use the down arrow on your keyboard.

Gilbert Van Cutsem: I think I am in control.

Eric Kavanagh: You are in control.

Gilbert Van Cutsem: Alright. Here we go. The cloud imperative — the sky is the limit, is it an urban legend, or what would you think about it? These are just a few talks and things to consider.

First, from the "what" front, you know, as we all know, I don't think anyone is doubting this. SaaS-ification is here to stay because the software actually never dies, it merely moves to the cloud, right? I think I said this before in the previous edition of this. Oh no, or Eric said that for me in a previous edition. And I think the obvious reason, and this goes back to Robin in a way as well, is that on the corporate side of things, the corporate timeline is pretty easy. The CMO always needs it all and he needs it now. So, he is all about time to market. So sad, it's a good excuse for that in a way for him. The CIO, however, is a little nervous about SaaS and clouds because, you know, the whole elasticity problem means that what goes up must also come down. You must be ready to scale out, but also to scale back. So, he is a little nervous about that. The CFO is not nervous, not more than the usual, but he goes like, "Hey, this is... how much will this set us back?" It’s the, you know, the infamous capital expenditure versus OPEX discussion. It's pretty old, but it's very, you know, very important in this world. And then, last but not least, is CEO, of course. He goes like, "Oh! Risk mitigation! Guys, you guys are all excited, but are we ready for this?" Because risk is what he thinks about.

So, what is the risk? Just a few thoughts, right? We are dealing here with thought leadership, but in an unfinished path because this is all pretty new stuff, all fairly recent stuff. We don't have a lot of data points, really, if you think about it. And so, we also, on the risk side, we have to deal with on-boarding, you know, people signing agreements go like, "Yes, that is what we want, the way to go," they sign up, but then that's not enough. You know, you have to on-board people and that, remember the movies? Back in translation, that's a little bit of, you know, what on-boarding is all about. And then also, as Robin just said, you know, on-prem is not necessarily going away right away. So, you have to integrate both worlds. It's a hybrid world. And so, how are you gonna do that? It's 80-20, the 80-20 rule Pareto, is that okay? Is that good enough? And then the garbage in/garbage out when you connect the systems. Is that okay? Is that durable? Because, you know, are you going to migrate, are you going to map your enterprise to the root system, how are you going to do that? And then the last one, which I think is extremely important, is multitenant architectures, meaning that data privacy on your own data, sometimes it's called "own your own data," becomes very important, you know? A hundred people using the same system, one database sits below the system, who's gonna see my data? Just me, right? Are you absolutely sure about that? Data privacy, data security helps up experts. If you’re the CIO, it brings back the "I" into CIO because now you are in charge of information. That's pretty interesting if you are a CIO.

So, let's talk a little bit about the "why." So, the strategic intent of all of this is very, very simple, I think. If you are a subscriber, there is market pressure. If you are a provider, there is competitive pressure. If you have peers, there is peer pressure. If you are a subscriber, it's just the market psychology. Everybody wants to go to the cloud, SaaS or whatever you call it, cloud SaaS, we all need and want to go there. And the reason is usually financial. That's the obvious reason, but if you think about the financial aspect, you get into what I call the bill-versus-budget paradox. Are you gonna go for a subscription, all-you-can-eat systems, $50, $500 a month or something like that, or do you dream about usage based so that you only pay for what you really use? And so, how is that going to work, usage based, consumption based? Are you going to meter all that stuff? It's probably not gonna happen right away. So, you will end up with a hybrid mechanism, which is, I pay 200 a month and maybe occasionally 500 because I have to pay for the extra consumption. Retainer Plus, it's probably going to, in my opinion, the way to go.

But, there is also something that I call the hidden intent on the wide front, and I believe that, you know, this is absolutely real. It's the change of control, it's the CIO versus the CMO, the power shift or the power struggle between the CMO, "I want it all and I want it now," and the CIO, who says like, "Hey, this is all about data, you know? I used to run, 20 years ago, it was all about hardware systems. Ten years ago was all about applications. Today, it's all about the data. And since I am the CIO — information — it's all about me. I am in control." So, that is kind of the power shift or power struggle I believe that is going on right now between these two, the CMO and the CIO.

So, in the end, this is all so young that nobody really knows if we are in the innovator type of environment or in the early adopter type of environment. I believe we are in the early adopter type of environment, not the early majority, just the early adopter, but, you know, kind of halfway. And so, you know, for the customer, the end user, the subscriber, this is about getting a head start because the CMO wants the head start, right? And so, it's important to not end up with what we call diminishing returns. The limiting head start might lead to diminishing returns. That's why it's extremely important to, you know, find, trust the parties that can make sure that single point of failure is not an issue and that data security is respected. So, it will require quite a bit of change management. And so, in the end — almost done, this is the last slide — how are we going to do this? How does the move to the cloud, the move to SaaS going to be, you know, seamless and easy? Well, by doing two things: paying attention — provisioning — really important, and on-boarding, even more important.

Eric Kavanagh: Alright...

Gilbert Van Cutsem: And in that case, the sky is the limit. Thank you.

Eric Kavanagh: Yeah. That was great. I loved the very provocative ideas, I like the way you kinda broke all that down. I think that makes a lot of sense. And let's go ahead and push Ashish's first slide and I will hand the keys to the WebEx over to you, Ashish. Okay, go ahead. Just click anywhere on that slide and use the down arrow on your keyboard. There you go.

Ashish Thusoo: Alright. Thanks, Eric. Hi folks, this is Ashish and I am going to be telling you about Qubole. So, just to start off, Qubole, essentially it provides big data as a service platform. It's a cloud-based platform hosted in the Amazon cloud and the Google cloud and we provide technology such as Hadoop, Hive, Presto and a bunch of others I shall talk about, all in a turnkey manner so that our clients can essentially get out of all the confusion in the big data infrastructure world or get out of actually running an operating this infrastructure and really focus more on their data and the transformations that they want to do on their data. So, that's what Qubole is all about.

In terms of the tangible benefits, one way of thinking about Qubole, you know, of course it's a turnkey, self-service platform for big data analysis and big data integration built around Hadoop, but more fundamentally, what it does is that, you know, for all the big data engines such as Hadoop, Hive, Presto, Spark, Chartly and so on and so forth, it brings all the benefits of the cloud to these big data engines and some of the key manifests that it brings from the cloud's perspective is, you know, making infrastructure adaptive and by adapting, I mean both agile as well as flexible to the workloads being run on any of these engines and also making these engines that much more self-service and collaborative in the sense that, you know, Qubole provides interfaces where you can use these particular technologies not just for your development or, you know, developer-oriented tasks, but even your other data analysts can also start getting the benefits of these technologies to a self-service interface.

We get a lot, you know, pertaining to this particular, you know, webinar, you know, this is one of our perspectives as to what benefits of the cloud that Qubole brings to big data. So, if you just do a comparison between how you run, say, Hadoop and let it workloads in an on-prem setting, in an on-prem setting, you are always thinking in terms of static clusters, you know, you fix your clusters, you maybe size them to your peak usage and you keep them there and then if you have to change them then you have to go through a whole process of procurement, of deployment, of testing and so on and so forth. Qubole changes that by creating clusters completely on demand, our clusters are completely elastic, we use the objects stored from the cloud to actually store data and the clusters come up and, you know, they come up on the basis of the demand being generated by the users and they go away when there is no demand. So, this makes that infrastructure that much more agile and flexible and adaptive to your workloads.

Another example of flexibility is, you know, today you might have created your static clusters here, you know, with a certain workload in mind and if your workloads change and your infrastructure now needs to be upgraded, maybe you need more memory on your machines and things like that. Again, you know, doing this on the cloud through Qubole for example, makes that simple. You can always rent new, different types of machines and, you know, get clusters, 100-node clusters up and running in a couple of minutes as opposed to weeks that you had to wait on for on-prem Hadoop.

The other key thing that in which Qubole differentiates itself from on-prem is that Qubole is essentially, as a service offering, so all the tools and the infrastructure that you need up to integrate the service, you don't have to... wherever on-prem, you know, it's primarily you take the software, you have to run it yourself, you have to integrate it yourself and do those all those benefits, all the benefits of SaaS model are a clue to, you know, how Qubole offers big data as opposed to running Hadoop on-prem by yourself.

This slide generally covers our architecture. We are, of course, based on the cloud, we store our data on objects in the cloud [00:25:13] in the cloud, Google cloud and Google Compute Engine or Amazon Web Services. We take all the Hadoop ecosystem projects and around that, we have developed key IP around auto scaling and self management, we have done a lot of cloud optimizations to make these component technologies work really well in the cloud as, you know, cloud infrastructure is very different from just running things on bare metal and a whole bunch of data connectors to enable data to be moved in and out of this platform. So, that compares the cloud platform and that enables that, you know, that is a key... the key feature there is how to make all the self service so that you don't have to have a strong... you don't have a very large operational footprint while running this, but we tie that along with our data workbench whether these are tools for analysts, whether these are data governance tools, whether these are templating tools, and so on and so forth so that you can bring the benefits of this technology, not just to the developers, but other business users and the enterprise as well. And of course, we tie in also this cloud platform to tools that you folks might already be using whether these are, you know, utilization tools or just Tableau or whether they are using, you know, more data warehousing type of products like Redshift and so on and so forth.

Today, the service is running at fairly large scale, we process actually close to 40 petabytes of data every month now across our client base. Our clusters vary in size from 10-node clusters to 1500-node clusters and, you know, in terms of the range of scale that we can process and by and large, to the best of my knowledge, we run probably some of the largest clusters on the cloud as far as Hadoop is concerned and we process to around 250,000 virtual machines in a single month across our clusters. Remember, our model is clusters on demand, which has tremendous benefits in terms of reducing your operational workloads as well as improving your [00:27:19] and so on and so forth.

Finally, you know, one of our, you know, this is just a sampling of how Qubole has been transformative to various companies. Pinterest is an example of our client. They were already on the cloud, they were running Elastic MapReduce on the cloud, for example, and the data usage there was fairly constrained. They would have about 30-odd users who could use that technology. With Qubole, they have been able to expand that to more than 200-odd users in the company which have seen expansion of big data use cases and it's really brought, you know, what we call the definition of an agile big data platform and that it's become really central to a lot of their analytics workloads.

So, just to close out, you know, that was a brief primer on Qubole. Essentially, our vision is how we make enterprises that much more agile around big data and essentially, we leverage the benefits of the cloud and bring them to bear on big data technologies around Hadoop so that our clients can leverage those benefits of agility and those benefits of flexibility and those benefits of self-service nature on the cloud to become that much more effective to their data needs. So, I will stop there and hand it over back to Eric.

Eric Kavanagh: Alright. That sounds great and now, I'll hand it over to Mike Miller of Cloudant. Mike, I am passing you the keys right now. Just click on the slide, here you go. Take it away.

Mike Miller: Looks like I have the keys. So, I'll apologize. I lost... I think I forgot to ship some fonts with my presentation. So, hopefully you can look past that and imagine it’s beautiful. But, yeah, this is fun. I have got a long list here, provocative things that I heard that I wrote down that I am eager to return to you in the panel. So, I'll try to get through this quickly.

So, I am gonna start by Cloudant. Cloudant is a database as a service, our cloud provider and actually, I don't even have the new logo. We were acquired by IBM not too long ago. And so, we are... I am gonna talk about our service and particularly focus on trying to make our users and customers agile in a fairly different way than the previous speaker.

Cloudant provides database as a service and other data-related services for people that build applications. So, we engage directly with developers and we focus on operational or OLTP data in contrast to the analytics that we heard from Ashish previously. And the point there really, Cloudant's entire value, which can be broken down into helping our users do more and so that's build more apps, grow more and sleep more. I will talk about them in a little bit of detail, but the general idea here is that if you are a user, you know, you are in a business enterprise, you are building a new application, adding a feature to existing application or web mobile startup, you should be focusing on your core competency. And previously, maybe up to a decade ago, IT was to be a distinguishing, you know, competition, sorry, competitive damage even running a database well to be a competitive advantage. Relieved that those days are over! And so, the way we really try to work with our users is to encourage them to use composite services, modular, reusable, composible with the idea being that reduces time to marketing, increases the scalability. And the overall idea here is that cloud is not just, you know, something new being pushed onto users, it's really a market... it's a market evolution because the way people build applications, consume applications, the devices on which they are running and the scale of data change pretty radically in the last 5-10 years. That's really stressed the existing application architecture for building apps as well as just dealing with that data and analytics workloads offline. And so, it opens up a whole stream of opportunity.

So, Cloudant is a distributed database as a service and it was unique, I believe, in its inception that it really shipped with a mobile strategy from the beginning, and I will talk about this in detail, but the idea is that writing applications now, you are not writing for just a single platform, right? You are writing for something I can run a petabyte scale in the cloud, it also has to be able to run smoothly on a desktop or in a browser and more and more we’re seeing things, we are having to run on a mobile device or a semi-connected device or wearable device or something we refer as IOT. And so, I think that, you know, applications that can deal well and leverage those different clients are incredibly competitive in the market and what we try to do is make it simple for people to single API in the single programming model to write, to handle data in all of those different devices that have vastly different scale. The interesting thing is, you know, initial uptake in web and mobile, this is where we saw our big subtraction, but even now before the acquisition, we are seeing larger and larger number of enterprise users even in things as what I say as conservative as fidelity investments, right, working with a virtual building, a virtual safe deposit box. So, I think that this market is actually taken off much faster than even we had expected.

Let's talk about cloud and a little bit more and then turn it over. The idea here is that we really make it easier for you to build more and use a service like Cloudant to store the database state of your application and then move that to your different devices and keep things in sync and start contrast on how you build application, traditional stack or you have to buy servers like we heard about before, where you have to provision those and install license things. With Cloudant, we try to make easy. All the data that you will need, all the search services, database, etc. for your application can be acquired by signing up and getting a single endpoint URL and then starting to use that URL. The idea being that, that is a service that uses multiple indexes, some multiple technologies underneath, some proprietary and many open source, but we use them together in a way that the end developer or product team needs to build something. And so, database analytics, very different than they did it in inception where you would have, you know, rows and columns to store business ledgers, now we need to start JSON documents that generally happens over HTTP or using existing open-source APIs and then finally, we give you the things that database should do like a primary index and secondary indexes for, you know, retrieval and LTT and then driving application logic. But in addition, there is a wide range of things like search, geo-special and replication between devices that are very important. So, that's all provided underneath our API.

But, the really distinguishing thing that allows our users to grow and, for instance, why Samsung was one of our earliest and biggest customers is that, you know, Cloudant now is underneath [00:34:14] cluster. Each cluster shares enough architecture of three to hundreds of nodes, but we run those in over 35 data centers now globally so that there is always a place for you to store your data within a millisecond of any other cloud provider or most existing data centers. So, one of the big early things that we are challenging in the cloud as well, is how do I split a hybrid architecture for my application service maybe here and my database servers maybe someplace else that will never work. They have to be on the same machine or in the same place. Well, the reality now is that by cobbling together different cloud providers, and this is something that we still do as an IBM company, you can make sure that your database is always within a millisecond of any other place and we take care of the peering agreements and just take down with the cost off the table, something that we worry about. So, Cloudant is really a database as a service, but you can think of it more like a CDN like [00:35:05] for your database for data that changes, you know, on millisecond time scale.

And really, finally, I think the major selling point is if you build an application that's successful, you have to decide as an organization whether or not if you want to then grow the 24x7, 365 globally distributed, you know, operation team that it takes to run that at the large scale to whether that's something that now is commoditized as well. And so we focus very heavily on helping on-board new users and new customers and help them make the jump to the cloud and build architectures that use cloud analysts and works everything in a very coherent and scalable way so that is the end, you know, our users focus on building applications and not on surviving their own success.

And with that, I will just say thanks, skipped over some slides that were skipped and I will turn it back over to Lawrence.

Eric Kavanagh: That is fantastic. So, Lawrence, let me hand you the keys to the WebEx here. Just give me one second. There you are. Keys being transferred. Just click on that slide anywhere and use the down arrow.

Lawrence Schwartz: Great! Well, thank you for the handover and, you know, thanks to all the presenters today. Nice way to set everything up and there will be a lot of things to talk about it as I get through with the presentation here. So, again, I am Lawrence Schwartz. I run marketing over at Attunity and, you know, want to talk about some of the issues that we see and then some of the challenges in the space that we are in.

So, a quick overview and introduction to Attunity as a company and who we are. We focus on moving data. So, we talk about moving any type of data anytime, anywhere and enabling that for users. We are a public company based out of the Boston area, or near Boston, and when we talk about the cloud, we have some great relationships, we are part of the AWS network, a big data integration partner, and we have been close to them since the launch of their Redshift, even working with them before that. We have gotten some nice recognition for the work that we have done and as a company, we are in over 2000 places use Attunity, and we are in half of the Fortune 100 companies. So, we got some good experiences.

As you can see on kinda of the bottom of the slide here, a big issue is you’ve got data that's generated from all different types of sources these days from traditional, you know, CRM systems, all different places on the Internet, all the different places where data could start and then it has to go to places to be analyzed, to work with and to be looked at and we spoke if, you know, getting the data, you know, where it needs to be. So, I am gonna talk about our solutions that we do specifically on the cloud and when you think about that, often times the data, we have somewhere on-premise. So, besides having relationships with places like Amazon, we have very close working relationships with places like Teradata, Oracle, [00:38:08] and Microsoft, all the places where data traditionally existed on-premise.

So, when you think about this, you know, and I think it was Eric who, you know, talked about on-boarding is the key to the whole process, right? I have been thinking about the issues to getting data on a system. Now, we are just some of the bottlenecks that exist today and when you look at the people moving data into a data warehouse or a database and to the cloud, we can see a lot of time is spent on what's called the ETL process, the extraction, transformation and loading of the data from where it resides to where it needs to go. If you think about getting the value on the data, that's not where you want to be spending your time and efforts, that's not the most productive area for a data scientist. And the flipside to that is this — very few people who are very satisfied with that process. It's no less than 20 percent. We really find that to be a big process. So, there is the real kind of painpoint bottleneck, if you will, in getting to the cloud and doing that type of on-boarding that people need to do and there's even, you know, real performance issues, you know, you could look at how do you get stuff into the cloud and if you want to get, you know, a couple of terabytes into the cloud, you could certainly ship it to the cloud and there are still places that do that with larger data sets, or a lot of the traditional methods, just don't have the performance to get their [00:39:34] to do that. So, it's a real, you know, painpoint in the marketplace as people think about how do they get and how do they move onto the cloud.

So, if we step back in and look at what that means or why that's there and, you know, how this has come about, you know, both Eric and Gilbert talked about the fact that, you know, the data that's on there today, that exists today, you know, on-prem is here to stay, you know, cloud is here to stay. So, that integration becomes all the more important and often times, people fall back on the tools that they have to move over data. Again, there is a lot of ETL or traditional tools out there to kinda move data over in batches, but there's a lot of issues with that. People find that traditional ways of moving data are very time and resource intensive to set up. They often require a lot of scripting, even if they are autonomous in some way, a lot of people, a lot of manpower. There's so many sources and targets, particularly on-premise today to move it into the cloud, you know, all the systems I mentioned earlier, Oracle, Microsoft, Teradata, some managing that whole part of it. And then, you know, looking at the performance as it moves over, being able to have the tools to make sure everything is building quickly, there is a lot of thought systems that exist today aren’t well built for that.

And then lastly, a lot of the way people think about moving data is kind of done in the batch process and if you are thinking about trying to do more in real time, that's not the most effective way, kind of using stale data that's not interesting to the organization. So, when you look at what Attunity does in this stage and how we think about it is, it's a different architecture that we are focused on, we really built this from the ground up and thought about when you have to go from Pentaho open-source database out to the cloud, how do you make sure that it's very easy and straightforward to do? So, that requires rethinking, how you do the monitoring and kind of set up for. It's making the whole thing just kind of a couple of clicks to get started. It's really thinking about the movement and optimizing the performance over the channel and working with just a wide variety of platforms because a lot of big organizations kinda have the best degree approach and a lot of different types of databases or data warehouses are ready in their environment. So, you have to think about it differently. You can't just do an extract, you know, dump the data out to some sort of information loaded somewhere. You have to kinda think about the architecture change, how you do the processing, do it more in memory and focus on a more performance version.

So, what does that mean and what does that look like? So, one key tenent to get to the problem with the cloud is, that things have to be easier to set up. You know, that screen there, it’s just some screenshots from how we do it, but it's, you know, 1, 2, 3, kinda pick your source and target, pick what you want to do, you want to do one time [00:42:25] CDC and then just go. It needs to be no harder than that, you know? I know we just, you know, saw the presentation from Mike and he talked about how easy it was for people to get started with Cloudant. It’s the same type of thing, you have to deal with, kinda get going in a few steps otherwise you will start losing the value of it. When you think about the monitoring and control of it, there are some great companies out there, I know you’re familiar with, like Tableau and others, who have done a great job in visualizing the end product of data and how to do it. But, you know, being able to visualize the movement process, the management or where's the data set on-premise, in the clouds and moving over, is there a lag, there is a vacancy. Having that viewpoint is critical and that's an important part of moving forward.

Another aspect that becomes important is the performance. You can't just rely on the standard FTP kinda two-way protocol that people have been using for years. As you move more and more data over, you have to have optimized, a file-channel protocol that is geared more towards, you know, one-directional movement most of the time after we think about how you break up tables and ship them out and move them over and you have to give people the flexibility to do that, otherwise you can't get it there in time and if you do that differently, think about it differently, you can get a 10x performance, but you have to rethink the technology.

And then lastly, as I mentioned earlier, you know, you have got a lot different places that databases exist today. So, you got to be able to work with all those and offer the widest kind of amount of support so that people can get onto the cloud. So, what does that mean for users and, you know, and those who are out there who wanted, two kind of quick cases of how people had challenges getting to the cloud, see the value, but then are able to do that if they have the right toolset.

So, one company that we work with, Etix, they do online ticketing, major provider in this space and I know Robin talked about data center offload is kind of a key in this case for the cloud. This is exactly what they are trying to do. They were trying to load and sync their data from Oracle on-premise to Redshift and do that in a timely fashion. And the interesting thing is, you know, go back to what Gilbert said, you know, it's really tough about on-boarding being an issue. They could see the intrinsic value of Redshift, they could see the cost savings, they could see all the advanced analytics that they quickly start doing that they continue for, they knew that value, but there was a roadblock to getting there. In this case, they looked at it and said, "Well, I see the value of Redshift, but it's gonna take them, you know, three months, development effort and time and, you know, maybe hiring the DBA and doing all this extra work to get there." So, there is a real block in the path to do it. Once you have the right toolset to do that, the right data integration capability to do that, they were able to go down from, you know, months of planning to literally just get going in minutes, and that's again lowering that barrier of getting people onto the cloud, we need to have the right capabilities to deliver on the promise.

The last, you know, slide I have here, and kind of another use case is, you know, we’ve worked with other companies, Philips, you know, well known in many spaces, we work with their health-care division and again, they were trying to go from an on-premise source over to Redshift, in this case SQL Server, and they knew the value, they knew all the analytics, they could do on it and they had done some testing on it, but they saw that without having the right tools, this is something that was gonna take them, you know, weeks and they had been spending actually weeks spinning their wheels and trying to get things moved over once they had the right tools that simplify, get it moved over quickly, they were able to go down and start loading in less than an hour, you know, over 30 million records. So, the real time went from couple of months to about two hours for them. And then they were able to do the things that they wanted to do. They didn't have to focus on the data loading, they could focus on the operational support. They got a much better matrix for all these care, cost and operations. So, you think about the whole challenge, you know, we design that spaces, enabling the data movement and now more than ever with the cloud when you think of it being kind of a remote place to pick your data, you know, this becomes an area that, you know, more and more people need to solve, to take advantage of what's out there. So, that's an overview of what we do and with that I will pass it back to you, Eric.

Eric Kavanagh: Okay. That sounds great. We’ve got a good amount of time here. We’ll go a bit long to get to some of your good questions, folks. So, feel free to send your questions and I’ve got a few questions myself.

Lawrence, I guess I will start off with you. You guys have been in this space of kinda supercharging the movement of data for a while and you have been watching the cloud very carefully and I’ve really been kinda surprised at how long it's taken major enterprises, Fortune 1000 companies to fully embrace cloud. I mean, there are, of course, pockets of severe interests, let's call it, in large organizations, but as a general rule, there’s been a bit of a reluctance that is only starting to wane in the last year or so, at least from my perspective, but what do you see out there in terms of cloud adoption and readiness of the enterprise to use cloud computing?

Lawrence Schwartz: Sure, I think you are right. It has been a significant change and it's certainly taken time, you know, they have that joke about, you know, that successful — overnight sensation — or really overnight success, that really takes years in the making, and that's been true for the cloud, right? It's... you have seen that kick in the last year, but it's due to all the hard work of a lot of players like Amazon who have been doing this for years, you know, to get the service adopted, the kind of, you know, prove the metal and there's, you know, failures and problems to give the diversity and flexibility that they have, that’s something that Redshift offers. So, I think the maturity has gotten there, the confidence has gotten there, you know, the... I think it's infiltrated into a lot of companies through small areas, you know, small use cases, small trials, kind of outside that kinda IT control and with that, you know, those successful kind of periphery projects have proven now, there's now more of a willingness to have the conversations about how that spread. And frankly, you know, there's been additional tool that has, you know, have also come out to make these easier, like what we do and, you know, there is that, not just move the data, but show the value of BI in the cloud, and showing that.

So, it's, in one way, it's an overnight or a big uptick in the last year, but a big part of that's been all the hard work of building up to that. So, now we as a company see a lot more adoption. It's as a business for what we do, it's grown quite a bit and the cloud, you know, we do a lot of on-premise to on-premise movement. Now, cloud shows up in a lot of the conversations as, you know, real business cases, real offloading cases out where a year ago was certainly, you know, just more exploratory. Now, they have got real projects to move. So, it's been nice to see that movement.

Eric Kavanagh: Okay. Great. And Mike Miller, you had mentioned that you heard a couple of provocative statements that you wanted to comment on, so, by all means, what do you find interesting or what do you wanna talk about?

Mike Miller: Oh, I think Robin, he made a point, his second-to-last slide contrasting where innovation counts. The cloud will always be second best and I'd love to hear a little bit more about that because in my mind, if I was thinking about building, you know, an application or some new service, it's hard for me to think that my organization, no matter what they are, really wants to go engineer-to-engineer with Google, Amazon, IBM, Microsoft. So, I think maybe I misunderstood his point with that.

Eric Kavanagh: Interesting. Robin, Mike has thrown down the gauntlet. What do you think?

Dr. Robin Bloor: Well, I mean the point here is that there are a number of situations that I’ve come across which... where people have gone into the cloud and walked back out and the reason they walked back out was, you know, when it came to actually having emotionally, this was performance driven, but the performance was actually the crux of the application is being built as they couldn't get the low latency they wanted and the cloud was of no use to them. And, you know, the situation was that, you know, actually going into the cloud, even if they were given the ability to measure behavior of the networks for them in the cloud and that workloads in the cloud with something they had absolutely no control over, and because of that, they couldn't create the tailor-made services that they were looking for, and that’s a performance edge. I don't think there's anything in terms of, you know, coding that’s going to be constricted, what you can do in the cloud. It's service level, it's a constriction... if that's part of where your critical capability is going to be, then the cloud is not going to be able to deliver it.

Mike Miller: Right. The... So, I appreciate that clarification. I do agree, actually, that transparency is one of the big things that here as desire right now from users across many different providers. So, I think you raised a very fair point. When it comes to performance, I think that traditionally it has been very hard to, you know, to go to a cloud provider or any given cloud provider and find exactly the hardware you are looking for, but it will noting kind of the upping the ante in the race to basically free storage between Google and Amazon and other competitors that it is and I think you see the pressure that puts on driving on the cost of SSD, flash, etc. So, I think that's a fun one to watch going forward.

Dr. Robin Bloor: Oh, absolutely correct, you know? I mean, I think there's one of the things that is actually happening is that the second wave is coming on. The first wave was this, you know, this wonderfully tailored services as long as, you know, it's a little bit Henry Ford; you can have it recolor as long as it is black, but, you know, even so, extreme reduction in certain kinds of costs of having the data center. Or, the second thing that happens is, having actually built these huge data centers out, they start these cloud operators, suddenly start discovering things that you can actually do. You couldn't do before because you didn't have the scale. So, there is, I think, a second wave which, to a certain extent, is going to make the cloud even more appealing.

Eric Kavanagh: Okay. Good. Let me go ahead and bring Ashish as I am gonna go ahead and throw up your architecture slide here. We always love these kind of architecture slides that help people wrap their heads around what's going on. I guess, one thing that just jumps out at me is, of course, YARN. We talked about that on yesterday's briefing. YARN is not a small deal. For those of you who aren't familiar with this concept, it is "yet another resource negotiator." It’s, really it's a very interesting development because what happened is in the Hadoop movement, YARN is kind of replacing the engine really, if you will. Our speaker from yesterday will refer to it as the operating system. It's like the new operating system of Hadoop, which of course, consists of the hybrid distributed file system underneath, which is basically storage when you get right down to it, and then MapReduce is what you used to have to use to use HDFS. MapReduce is an absurdly constraining environment in terms of how you get things done. So, the purpose of YARN was to make HDFS much more accessible and make the entire Hadoop ecosystem much more flexible and agile. So, Ashish, I am just gonna ask you in general, since you are mentioning YARN here, I am guessing that you guys are YARN compliant or certified. Can you kinda talk about what... how you see that change in the game for Hadoop and big data?

Ashish Thusoo: Yeah, sure. Absolutely. So, I think, you know, there are two parts to... So, let me first talk about, you know, why YARN was done and then talk about how that potentially changes the game and what's fundamentally still is the same, you know, where it doesn't change the game. I think that's an important thing to realize also because many times you, you know, you get caught up on this hype of say, this is the new, shiny thing and, you know, everything is going to, you know, all the problems are going to go away and so on and so forth. So, but the primary thing is that, you know, the strength and the weakness of the MapReduce API was that it was a very simple API and essentially, any problem that you could structure around being a sorting problem could be represented in, you know, that API. And some problems are naturally, you know... can naturally be transformed into that and some problems, you know, you sort of, you know, once you have just MapReduce at your disposal then you try to fit into a sorting problem.

So, I think the latter is where YARN plays a role by expanding out those APIs by, you know, being able to compose, you know, maps and reductions and, you know, whole bunch of different types of APIs in terms of how the data can be distributed between these two stages, and so on and so forth. You just made that API that much more richer. So, now you have at your disposal, different ways of solving that same problem, right? So, you just don't have to, you know, be constrained by the API and the problem gets solved one way or the other like, you know, if you are, you know, trying to do an analytics, you know, workload, you can express that in MapReduce, you can express that in YARN. The big difference that happens, that starts to happen is, you know, in terms of, you know, the performance matrix that you start seeing, you know, once you start, say programming to YARN and in some cases, a newer set of things, for example, streaming analysis and so on and so forth starts becoming a reality when you start, you know, doing that, you know, those things in YARN.

So, those are the differences that, you know, that thing has brought into the ecosystem. I think it's much, the richness there is much more on the API side as opposed to it being another resource manager, especially in the cloud context. If you think about it in cloud context, the resource manager is actually your... the VMs that you bring up, you know, you have virt... you know, it's not necessarily... Again, this is a big difference between say, on-prem how you are running Hadoop clusters and how you are running in the cloud then, you know, you have like the constrained static set of machines, you want to distribute those machines amongst different resources and they were used for YARN there. But, in the cloud, you know, you can bring up machines left and right. And so, just from the perspective of being a resource manager, it probably doesn't have that, you know, that bigger need and specifically in the cloud, but from the perspective of providing these, you know, richness of APIs which allow you to, for example, the Hive is initiative they can now program Hive to not just to use MapReduce, but have much more richer plans of doing jobs and things like that. It brings those benefits to the ecosystem. I think that is where the true value of YARN belongs. And in the cloud context, definitely, it's not that interesting from the resource management point of view, but it's much more interesting in terms of what it enables other projects to do, in terms of, you know, workloads that now, it now can be used to be programmed on to your data or the previous workloads that can be done in a much more efficient way.

Eric Kavanagh: Right.

Ashish Thusoo: I had, you know, one more just, you know, adding to Mike, you know, there was another provocative thing which was said which is around and, you know, which was around, hey, treating the cloud as yet another data center. I think you... you know, that is one point of view which most companies, you know, look at and say, okay, you know, that's the easiest point of view actually to look at saying that, okay, you know, this is, you have bunch of machines on your, you know, you have compute, you have storage and you have networking on your on-prem data center and cloud provides the same thing out there. So, I am just going to do exactly the same thing that I am doing on my own on-prem data center and do the same thing in the cloud and viola — that's how it should work. What we have found out, you know, having been running the clouds for, the two clouds where, you know, you have the ability to provision VMs within a minute, the ability to use a highly scalable objects to store data and things like that. We have found that cloud actually, the cloud architecture and these inherent abilities actually enable different ways of doing things, you know, and this is what I have talked about in my slide as well, you know, the whole notion of... in just, you know, in... the perspective of just Hadoop, the whole notion of just running the static cluster versus on-demand dynamic clusters, that is something that you don't see happening in an on-prem data center, you know, versus, you know, true cloud where the, you know, there's a enough capacity to be able to support these types of workloads.

And so, I think there is definitely some shift needed. You know, the big fear for me is that if you just treat cloud as yet another data center, you actually... while you, you know, there are lot of other benefits, but there are lot of intrinsic benefits that you might ignore if you, you know, start doing that, security is another one, the way you deal with security and the cloud, there's a lot of differences in terms of how you would deal with, you know, in... from on-prem perspective and so on and so forth. Just wanted to add that in, from my perspective.

Eric Kavanagh: Sure. Yeah. No problem. We have one attendee asking about various types of use cases like logistics and specifically HR, so I threw up this website of Workday, wanted to make a couple of comments on that, and then Gilbert, maybe I will bring you in to comment on the whole concept of architecture. So, in terms of HR, I actually heard a rather well, I will call it, let's say comment from an analyst a couple of months ago, a few months ago I suppose, about going to the cloud for Human Resources. I have been doing some research on this to know lot of HR-type functions are being outsourced to the cloud, certainly stuff like payroll is fairly easy to outsource these days, benefits programs and insurance, that kind of thing, but there is a real serious caveat to keep in mind and Gilbert, this is what I want you to comment on from an architectural perspective, which is you have to be very careful about when you are moving to the cloud for some kind of critical business service because you either want to be very strategic and very thoughtful, meaning you go through the process of making sure that you understand what's going on in the cloud and what's staying on-premise, and there is the folk from Attunity will tell you that truly one of the things they specialize in is making those connections such that they provide the kind of connectivity you need because what's happening with some organizations is they go and they will use Workday for example, to put some of their HR stuff to the cloud, but they don't do it all or they don't do enough or they don't think through it enough, and what happens then? Then they want to happen to manage the cloud environment and their original on-premises environment as well, which means, guess what? He just increased your cost, you doubled your workload and you created lots and lots of headaches for people, and that’s usually when someone gets fired and then the guy who comes in has a real mess to clean up. So, you really do have to think through the architecture of the data and the systems and the processes and make sure you dot all your i’s and cross all your t’s and with that, I will throw it over to Gilbert for comments. I am guessing it will be with that, but maybe not.


Gilbert Van Cutsem: Alright. Yeah. So, just another example of something similar, just yesterday happened to me. So, I lost one of my doctors because he went out of business. I don't know. It sounds amazing. He was a chiropractor and he went out of business. I don't know why, but, the thing was this — I have no chiropractor and I like to go to a chiropractor, you know, occasionally. So, I find a new one and it's close to, you know, close by and all that. It's all good. And so, they go, as usual, you have to do all the paperwork and let us know if blah, blah, blah. But, the good news is we have a new system because, you know, we’re on the Web now, in the cloud. It's all cool. I go like, okay, you know, and they send me a link and I have to do all the paperwork online, which is fine and I put all kinds of things in there about, kind of secret like, you know, social security numbers and that type of stuff and who I am, how old I am... all my details. I put it all there and I submit because of course, I do believe in technology.

And then I walk up to the office, the next day for my first appointment and they go like, "Did you do the form?" I go like, "Yes, Ma’am, I did." "Okay. Then we will go and find it." I go like, "Well, I did do it." And she goes, "Yes, we know because you are the fifth person today to walk in, to walk up to me and complain about that's not finding the form." And I go like, "But, you can't be serious about that. This is pretty confidential information. Where is it?" This happened to me yesterday, yeah, which brings back the whole issue and the whole idea of who owns the data really, right?

I know you move to the cloud and people get onboard it into a new system like in this case, my chiropractor and they subscribe to a new system. It's in the cloud, it's all safe, it's fully multi-tenant, they used to have it on-premise system, all the data was moved into the new system, but now apparently, they can't get it out.

Eric Kavanagh: Yeah. That's not good.

Gilbert Van Cutsem: So, I don't know where my data is and assume she gets really mad, right? She goes like, "Oh, this is impossible. I pay you money and my customers are, my patients, sorry, are unhappy and with the data is gone, I wanna get away from you. I wanna go to a different system maybe also in the cloud, right?" How do you then move the data of your patients in this case, the data your business owns, to another system? How do I get it out first of all and then load it again? I am sure ETL in the cloud is an answer somehow and we have experts on that, but it's not that easy.

Eric Kavanagh: Yeah, but that's exactly right and folks, I threw up this other slide here, this other, another screen to show you where you can find the archives. So, anytime you want to check out — oh, there’s the inside of our website, I don't want to show you that. So, here is the main website and on the right column here you can see a different show. So, TechWise is right here. You click on that and on these different pages where we will actually post the archives. So, we do archive all these webcasts.

Actually, I wanna throw back over to Mike, I suppose, and then also to Lawrence to kinda comment on this story that Gilbert just told. So, Mike, there is some, kind of, now this is kind of a small-business concern. You guys are more focused on big business, but nonetheless, if a large company who works with you and they want to go somewhere else, how do you manage that movement of the data and securing the data and so forth?

Mike Miller: Yeah. That's a very good question. It's one that used to come up a lot more often than it does now in sales calls, which I find to be an interesting anecdotal piece of evidence for a call. You know, I think that first of all, we are talking about a lot technologies, or at least employment models that are relatively new. This is very early in the cloud, right? We are talking about things like cloud, or in the case of data, we are talking about analytics services like Hadoop for databases and then NoSQL or NewSQL formats. You know, these are fundamentally new technologies and especially around things like, Hadoop and NoSQL, all of the ancillary services, the connectors, right, the... you know, if I want to find somebody that consults on Oracle, that's something I can find, but that entire ecosystem is just kinda spinning up right now.

So, it's getting easier day over day to say, okay, you know, give me a service that can read from 'x' traditional system, put it into Cloudant and do something with it and then put it back into 'y' traditional system, right? So, now they are very, you know, there are quite a few those things and it's actually more challenging, I think, for a typical user to understand what is the best choice, right, if I want to connect all the new technologies on-prem and then in the cloud.

So, I think as a cloud vendor, it's really on us to be very opinionated about that and to help walk users through the landscape of possibilities because the shift's a lot of new and I think that the average user, whether it's a CTO, CIO or whether it's actually developer, is coming up that learning curve fairly quickly. I think that a lot of the kind of baseline stuff is being worked out, cross-cloud connectors and, you know, taking away the really most basic worries about say, you know, bandwidth cost and whether or not you are going out on the wide area network versus staying on, you know, VPN the entire time. A lot of those things have been kinda abstracted away and what is the true promise of the cloud.

But, in general, I think you are also seeing, you know, that anecdote that we heard was, you know, something that is probably isomorphic to, you know, what will happen to your buying into a brand, you know, in a past lifetime, you know, what happens if that brand doesn't deliver, how much can I really trust that brand? I think you are seeing exactly the same thing happen in the cloud and, you know, I think that companies like Microsoft, Amazon, IBM and Google are, you know, very much stepping up and saying that there will at least be multiple pillars of trust and making sure that you are not going in with a company that's going to dry up and swallow your data, or worse, lose it or distribute it, right? And so, they are, at least, they are independable and they are anchoring, you know, the development of such ecosystem. But, I say to close, it's very early and a lot of that tooling is just getting started and, you know, I think you are going to see consulting services, you know, really putting a lot of focus on that in the very near term.

Eric Kavanagh: Yeah. That's a really, really good comment you just made there. I like that "pillars of trust" concept because the other thing to keep in mind here is you do once again have a number of fierce competitors vying for market share and for IT span, it's just like the old days all over again. Really, in the old days, by which I mean last year, you had IBM and Oracle and Microsoft and SAP and then Computer Associates and Informatica and all these companies, Teradata, etc. In the new world, now you have got, of course, Microsoft with their Du Jour, you have got Google, you have got Amazon Web Services, you know, you have Facebook in certain context. So, you have all these companies that are not necessarily so excited about working with each other, but you do have things like APIs. And so, one of the nice things that APIs really are crystallizing into the connectors that hold together the larger cloud, I suppose, and I want to throw up a slide for Lawrence to kinda comment on all this.

Yeah, Lawrence, obviously, you guys have specialized in the space for a while. So, I think you do have awesome advantage over maybe some newcomers. But, nonetheless, these are all very serious concerns because how data gets stored in the cloud is different than how it gets stored on-premise. Then I think that Mike makes a really good point that this whole space is just starting to take shape and it's gonna take a while for things to seriously fall into place and to crystallize. So, what's some advice that you have for companies that you... I guess, you basically concur with Mike, or what do you think?

Lawrence Schwartz: Yeah. I think it's, you know, what we see is when people are taking advantage of the cloud for a lot of use cases as compared to on-premise, you know, they are looking at kind of, you know, two different things. One is, they are looking at, you know, as we talked about this a little bit earlier, how do I... how does it incrementally add value to what I do, how do I, you know, how is it kind of an add-on? And so, you know, when back to when I talked about the Etix as a company where, you know, they are not moving all their operations over to Redshift, you know, yet per say, but they’re saying, "I do a lot of work on Oracle, I wanna offer some of this to some kind of analytics from different environments, you know, kinda figure out, maybe do some sandbox stuff there, and, you know, and then learn about my business that way, and that way they can kind of carve out what they want, move it over there and do the work and, you know, it's less of a concern with moving, you know, everything over and all the records and whatnot. So, I think they look at that as one way that to take advantage of it with having less issues.

I think the other thing is people are also looking at these cases that are and aren't excellent fit for the cloud that are very, very hard to do in other ways. So, I will take another example, you know, we work with a company called, you know, iN DEMAND. They are video on-demand player. They do this work for Comcast and all of this and they will actually, you know, take the data that they are working with, they will take the media files and they will supply it to the cloud for doing their processing, do their processing there, and then they will consume it back for their on-premise customers. And then, you know, that gets upstairs to third parties that consume reviews. So, it's, you know, if you want to think about how the company is approaching it, it's, you know, how do I get my... how do I add value, how do I maybe not move the whole business at first, how do I get the right use cases, how do I add incremental value to what I do? And that helps kinda build about the confidence on what they are doing and as part of the process, and of course, you know, a key piece of that is, you know, making sure that they can do that securely and reliably and, you know, we make sure to [01:12:17] the latest levels of encryption and other things to take care of that as much as we can on the transport side. But, that's how I think a lot of companies are approaching the problem.

Eric Kavanagh: Okay. Good. And maybe Ashish, I will throw one last question over to you. I am just throwing up, actually, I like your architecture slide. Even this slide I think is pretty neat. So, one of the questions in, you know, HDFS of course, by design the default is to save every piece of data three times. You can adjust that, of course, you can make it twice, you can make it four times, that does provide some overhead over time, obviously, but it is a way of backing up data. Anyway, that was the whole idea, one of the key ideas, right, from HDFS originally is redundancy, is not wanting to lose data. I’ve kind of been wondering how that's going to affect things like replication servers, quite frankly, when Hadoop does that natively.

But, one of the attendees is asking — "Can you request physical backups like tape for your cloud data? I read of a company that had their cloud management console hacked and their data and online backups trashed."

You know, we are hearing about these breaches all the time, they are getting more and more serious, they are killing major brands like Target, like Home Depot, etc. So, security is an issue and backup and restore is an issue. Can you kinda talk about how you guys address things like backup and restore and security?

Ashish Thusoo: Yeah, sure. So, we... So, I will talk about that and talk about HDFS first. So, as far as Qubole is concerned, you know, we... since we work on the cloud, we use the objects store there to store data. So, again, this is one of the other key differences why, you know, big data service on the cloud becomes different from on-prem. On-prem, we have always talked about, you know, HDFS and so on and so forth, but if you go to the cloud, a lot of the data is actually stored in their object stores. For example, that could be an S3 on AWS, Google cloud storage on Google Cloud, on Google Compute Engine, and so on and so forth.

Now, many of these object stores have built-in capabilities of providing you things, you know, these object stores, by the way, you know, one of the big differentiators from real clouds to actually your own data center is the presence of these object stores and the reason that these object stores are cool pieces of technology, you know, they are able to provide you very cheap storage and along with that they are able to provide you things like, you know, having the ability to actually have a disaster recovery thing built in and, you know, as part of that interface, you don't have to think about it. And also, they have tiered, you know, there is tiering there as well. For example, S3 has high availability and it's online access, but it's much more expensive. It's more expensive than say, a glacier storage on AWS, which is low, you know, it gives you, you know, the turnaround time is like four hours or something like that and it's much cheaper. So, you start thinking of, you know, those types of services. I think cloud providers are essentially providing those types of services to augment the need for things like tapes and so on and so forth. And also, to provide you disaster recovery or rather, you know, replication built in into these systems so that, you know, you are protected from disasters, regional disasters and things like that.

So, that is what Qubole heavily, you know, depends upon and the great thing is that a lot of... all the cloud providers are providing this. These are fundamentally very difficult problems to solve and by being built into some of the object stores that these cloud providers provide, you know, that is one more additional reason of, you know, storing this data, you know, in some of these object stores and using the cloud for that as opposed to trying to, you know, figure out, you know, replication, running two Hadoop clusters across different, you know, regions and, you know, trying to replicate data from HDFS from one region to the other, which is doable, we did that a lot when I was back at Facebook running this stuff there, but, you know, fundamentally, the object stores in the cloud just made it that much more easy.

Eric Kavanagh: Okay. Great! Well, folks, we’ve burned through an hour and 15 minutes or so, a lot of great questions there and a lot of great presentations. Thank you so much to all of our vendors today and of course, to both of our analysts on the show today. A big thank you, of course, to Qubole, Cloudant and Attunity. We are gonna put the archive up at insideanalysis.com. I showed you where that goes, and big thanks to our friends at Techopedia as well.

So, folks, thank you again for your time and attention. This concludes Episode 3 of TechWise, our relatively new show. There is Episode 4 coming up pretty soon. It's gonna be on the big data ecosystem. So, watch for information on all that. And then till then, folks, thank you so much. We will catch up with you next time. Take care. Bye-bye.