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Top 5 open source tools for big data

With the amount of data sweeping in, thanks to the internet, cloud computing, social media and mobile devices, organizations are now facing the challenge to manage and utilize this data. The impending question of how to use this data most efficiently now has an answer. Various open source tools have made it easy for organizations to handle the huge amount of data that they acquire. In this blog, we have listed top 5 open source tools for big data.



Any discussion about big data definitely follows the mention of Hadoop. Apache Hadoop as a data processing software is so efficient that at time we end up using ‘hadoop’ as a synonym to ‘big data’.It supports multiple operating systems: Windows, Linux, OS X .
Hadoop’s MapReduce is developed by Google. MapReduce website quotes “a programming model and software framework for writing applications that rapidly process vast amounts of data in parallel on large clusters on compute nodes.” MapReduce is independent when it comes to OS, and it is not just used by Hadoop only but by other data processing applications as well.
If Hadoop and MapReduce are being spoken of, mentioning R is vital. Revolution Analytics quotes R as the tool data scientists are looking for to “solve their most challenging problems in fields ranging from computational biology to quantitative marketing. R has become the most popular language for data science and an essential tool for Finance and analytics-driven companies such as Google, Facebook, and LinkedIn.”


At present it is managed by Apache Foundation, but it was originally developed by Facebook. This NoSQL database comes handy to organizations dealing with huge and active datasets. Third-party vendors provide commercial support. Like MapReduce, Cassandra is also OS independent.


This NoSQL database was invented to manage humongous data. Features include: complete index support, document-oriented storage, replication, high availability and much more. You can get commercial support at 10gen. Supporting operating systems include: Linux, OS X, Windows, Solaris.


GridGain comes as an alternative to MapReduce. It is compatible with Hadoop Distributed File System. There are two ways of getting access to GridGain: either you can download it from GitHub or buy the commercially supported version from here. Supporting operating systems are: Windows, Linux, OS X.


Neo4j is defined as world’s best graph database. Neo4j website describes it as “a highly scalable, robust (fully ACID) native graph database. Neo4j is used in mission-critical apps by thousands of leading startups, enterprises, and governments around the world.” Supporting operating systems are Windows and Linux.

Learn more about big data and it’s tools like hadoop and MapReduce from us to be more adept in managing big data.


1 Comment

Ranjith Kumar


The above information is very usefull. Pleas keep posting.

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