It is only through big data analytics that the actual value of big data becomes clear. But, these analytics require statistical and technical knowledge to implement any big data solution. So the assumption has been that you have to be a data scientist to extract meaningful insight from big data. This is where Apache Drill comes in. It provides the flexibility to do big data analytics on Hadoop without needing to have the knowledge of a data scientist.
Apache Drill – What is it?
Apache Drill is a software framework which can churn big data and deliver the insights you need, hiding beneath the petabytes of data sets. Technically, Apache Drill is an open source, standard ANSI SQL which can be used as a low-latency query engine on the popular Java-based programming framework Hadoop.
It can also work with a herd of budding NoSQL databases like MongoDB, HBase and also with cloud data servers, like Amazon S3 and Google Cloud Storage. Added to these, it also beats the level of other industry standard APIs (application programming interfaces) like ODBC/JDBC and RESTful APIs.
Apache Drill is often known as the open-source version of Dremel, an interactive data query system created by Google, which is the backbone of its popular IaaS (infrastructure as a service), BigQuery. Apache Drill features the same data-fetching speed as BigQuery and it can churn trillions of data tables, housed within thousands of database servers, in a flash.
Apache Drill is an ideal framework for those data-hungry applications which support the vision of next-generation distributed or edge computing. So, versatile data query software is the bottom-line requirement of these distributed applications.
Now a Java-based data processing framework like Hadoop can process larger data sets in a distributed computing ecosystem, and all of the sudden, big data and Hadoop have become so interlinked that they are often spoken of in the same breath.
How Apache Drill Makes Data Analysis Easy
So, what exactly is the specialty of Apache Drill?
Actually, it has many.
Firstly, Apache Drill has all the regular features of a structured query language. So, its users can use it as a regular SQL engine on their data-based app. Secondly, it can query a wide range of structured or semi-structured data types. So, it can hit the standard of popular business intelligence tools and work with them.
Now, analyzing big data can be a pesky task, as it demands a particular level of expertise from the person who wants to dig deep into big data. Thankfully, Apache Drill can be the beacon in the dark, as it combines data from more than one active source in the runtime of a single query.
Moreover, with Apache Drill, scaling is another breakthrough. Its communication range goes from a single node to multiple colossal server clusters. Regular users can simply dump Apache Drill on a standard laptop and can execute all of these groundbreaking processes.
Apache Drill and NoSQL Databases
In the arena of big data, it seems that NoSQL is the future of this ever-evolving world. The information world is becoming more gigantic with each passing day as cloud servers are busy registering every single update of human civilization. Web data has already annexed "big" from its name and in the near future it will only get bigger.
But, what does NoSQL have to do with that?
Admittedly, the main focus of Apache Drill is the non-relational databases as the growing volume of data on the Web also signifies that variation within the different data types or formats is also growing. So, with time the growing volume of big data is not only becoming unmanageable but also becoming more unknown.
The discrepancy among different data types is changing proportionately with the maturity of the Internet users across the world. Therefore, known relationships among various datasets are becoming more imbalanced with time. That's why NoSQL databases are on the rise and to cope with this, Apache Drill is the ultimate weapon.
Apache Drill for Data Complexity
What can be defined as "complex data?"
Simply, they are those datasets, which are difficult to read as far as a data query language is concerned. Any dataset without any associated schema value can fall under this group. Schema values are like a nomenclature of different data types. So, without any schema value, which is pretty obvious in NoSQL databases, it is extremely difficult for a query language to identify and fetch a particular data record from any database.
On the contrary, the main focus of Apache Drill is to work with datasets which are complex in their nature. Along with schema-based data formats, Drill can easily work with schema-free JSON data models which are similar to NoSQL databases.
Apache Drill can be tagged as a self-service data exploration tool, as it does all the heavy lifting of discovering data schemas while querying on them. Moreover, it can fetch data from the multiple formats of data sets and ensure an interactive data query analysis on the petabyte scale.
Moreover, Drill has got its own set of optimizers which can recognize different databases and it also has the ability to modify the whole query plan to harness the internal processing capabilities of a particular type of database. Flatly, Drill's architecture is versatile and pluggable to any kind of database.
At the end of the day, it’s actionable insight that industry leaders want, as it has an answer to all of their queries about their future, and they need it fast. Nowadays, where every passing second is more precious than the previous one, speedy information retrieval has already become the norm.
Admittedly, big data is gradually becoming the only food for the data-hungry enterprises or organizations who want to design their future based on a deep analysis of it. Now, every marketer wants to make an informed decision and only a set of standard business intelligence tools can help them with that. Apache Drill belongs to that group, and is helping businesses analyze their data in innovative new ways.