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What is the Influence of Open Source on the Apache Hadoop Ecosystem?

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Open source is at the heart of software development, giving creators free reign. This is especially true with Hadoop and its many facets.

One of the main reasons the Hadoop ecosystem is such a big success is that it is a free and open big data software framework. Software developers can access and modify its source code to create their own big data products or applications. Hadoop has resulted in the creation of several big data analysis applications. At a time when big data is defining our lives, it is probably fair to say that Hadoop has been defining how big data should be analyzed. This has been possible mainly because the Apache Hadoop ecosystem derives its principles from open-source software values. In this context, it is quite pertinent to determine the principles that inspired the Hadoop ecosystem. The salient principles are discussed below.

Salient Open-Source Principles that Inspired Apache Hadoop

  • Access to the source code — According to open-source principles, open-source software’s source code must be available to anyone for both modification and enhancement. A software developer can even create software applications using the source code. So the Hadoop framework is being reused and modified to develop several software applications around it.
  • Collaboration — Quality open-source software is created when multiple people put their heads together. Collaboration can give birth to new ideas, solve complex problems that someone working in a silo probably cannot, and uncover new ways of viewing a problem.
  • No discrimination against any interest — According to the open-source system, anyone can edit the source code, create a software application and give it away for free, sell it or use it for research purposes. This principle inspires the creation of several software applications that are either available for free or are available commercially.
  • License is technology-neutral — Open-source license terms and conditions do not favor any specific technology or programming language. The source code can be used to develop software applications on any platform.
  • No restrictions on software used — Anyone accessing the source code and developing another software application is free to use other software or other source codes.

Influence of Open Source on the Hadoop Ecosystem

The Hadoop ecosystem is a comprehensive, well-organized arrangement that makes big data analysis simple and accurate. The Hadoop ecosystem comprises several software applications, each specializing in a specific task. However, while the entire ecosystem is a combination of software tools, each of the tools in itself is capable of doing a specialized job independently. This means that you can pick and choose the specific tools needed to fulfill your purpose — Hadoop is that flexible. Hadoop does not bind you by rules that compel you to use the software in a certain way. You can use the source code in any manner you like.

Let’s take a look at an overview of how the Hadoop ecosystem works and also how it embraces the open-source principles along the way.

Let’s start with a basic definition of Hadoop. According to IBM, “Apache Hadoop is an open source software project that enables distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software’s ability to detect and handle failures at the application layer.”

How does Hadoop work? The Hadoop ecosystem comprises different units and each unit performs a different job. The different units are:

  • Hadoop Distributed Filesystem (HDFS) — The HDFS is Hadoop’s big data storage system. You can store enormous volumes of data and take data out at the time of processing. To store data, Hadoop uses a distributed framework where the data is stored across a number of commodity servers. The arrangement is such that even if a server goes offline, it does not disturb the whole setup; it is business as usual. That is what makes Hadoop such a resilient system. While the HDFS is Hadoop’s own data storage facility, it can also use external file systems to store data.
  • MapReduce — The MapReduce application analyzes and processes the big data the HDFS stores. It pulls out data from the HDFS without needing to use the industry-standard SQL or other query languages. MapReduce employs other Java-based applications to process data.

The Hadoop ecosystem offers speed and reliability because the data storage and analysis is not dependent on any of the several commodity servers that host data. The big data as well as the HDFS and MapReduce are stored in each commodity server. So, even if one or more servers go down, the work is not disrupted. The assumption here is that servers can malfunction at any time and that cannot be stopped. So, a system needs to be in place that makes sure that the work is not disrupted in the event of a server malfunction.


A great feature of Hadoop is its flexibility. To develop software applications, the users of Hadoop do not necessarily need to use the HDFS or MapReduce. For example, the Amazon Web Services system has adapted its proprietary S3 filesystem with Hadoop without needing to use the HDFS. Similarly, DataStax Brisk is a Hadoop application that is not using the HDFS. It is instead using Apache Cassandra’s CassandraFS. So you can already see how the principles of the open-source system have inspired the Hadoop ecosystem.

It is not difficult to identify how open source has influenced Hadoop. It is probably safe to say that the Hadoop ecosystem is going to write the rules of how big data should be processed in the future. This will be the case as long as Hadoop stays true to the values of open-source software. Open source is the spirit and soul of the Hadoop ecosystem. No matter how robust or intelligent a software tool is, it cannot gain universal acceptance without giving or sharing with the global software community.


Currently, open-source software is a major point of attraction to all the software communities. Apache Hadoop is one of the most successful open-source platforms. The associated Hadoop ecosystem products are also based on open-source software. The open-source philosophy is sure to gain in popularity in the near future, which means that we can look forward to many new software platforms.


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Kaushik Pal
Technology writer
Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…