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Hadoop is the hot new technology and SQL is the old, tried and tested tool for diving deep into big data, for analysis. This is true, but the number of projects that are putting an SQL front end on Hadoop data stores shows that there is a real need for data querying high level languages in the Hadoop environment. Hadoop MapReduce being a complicated tool for data analysis, developers had come up with Pig and Hive – similar to SQL, which makes it easy to implement Hadoop, without the need for coding in Java, to analyze data.  It is important to understand how different these are from each other – this is so that each can be optimally utilized for the right use case.

In the present age of Big Data, a number of querying options are available. While the old giant SQL continues to rein supremacy, organizations’ affinity towards open source programming and querying languages to tame Big Data has created plenty of space for Apache based Pig and Hive. Choosing the right…

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