[MapR Talk] Going Beyond Apache HBase: What We’ve Learned from Running Analytics and Operations in the Same Platform

Document created by aalvarez on Nov 30, 2015Last modified by aalvarez on Dec 7, 2015
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Apache HBase is THE Hadoop database, a distributed NoSQL database built to run on top of the Hadoop Distributed File System (HDFS). Those who use it love it for its scalability, wide-column flexibility, strongly consistent data operations, and of course, its tight integration with Hadoop. It is no surprise that it is one of the most popular NoSQL databases used today. Anyone deploying an analytics platform based on Hadoop should take a serious look at HBase to handle operational and unstructured data.

But HBase is not without its challenges, through no fault of its own. Considering the limitations it must overcome by writing to an append-only file system, it already performs some significant I/O magic to run like it does. This technical overview of MapR-DB explains how MapR used HBase as a springboard for creating a technologically advanced in-Hadoop NoSQL database.


KEYWORDS: HBase, NoSQL, Schema Design, System Internals


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