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A case study on why Facebook has opted for Hbase over Cassandra?

Published on 11 March 15
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Knowing what your users are doing on your site in real time and matching what they do with more targeted information transforms into better conversion rate and better user satisfaction, which means more money in the end. That's been one of the primary drivers for the transition of many of the batch oriented analytics system into real time. Facebook real time analytics system is a good reference on that regard.

In this session we will understand and learn from Facebook's experience and the reason they chose Hbase over Cassandra, and how we can build our own Real Time analytics system, achieve better performance, and make the deployment and scaling significantly simpler using commonly used Java API and frameworks such as JPA and Spring on top of a scale-out architecture based on Cassandra and GigaSpaces.

Knowing what your users are doing on your site in real time and matching what they do with more targeted information transforms into better conversion rate and better user satisfaction, which means more money in the end. That's been one of the primary drivers for the transition of many of the batch oriented analytics system into real time. Facebook real time analytics system is a good reference on that regard.

In this session we will understand and learn from Facebook's experience and the reason they chose Hbase over Cassandra, and how we can build our own Real Time analytics system, achieve better performance, and make the deployment and scaling significantly simpler using commonly used Java API and frameworks such as JPA and Spring on top of a scale-out architecture based on Cassandra and GigaSpaces.

This blog is listed under Open Source , Data & Information Management , Digital Media & Games and E-Commerce Community

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