Committing Hive Driver into Apache Cassandra
We released Brisk a number of months back with the objective being to give our community something that offers a great foundation for coupling together all the benefits of Hadoop with the power of Apache Cassandra. The marriage of Hadoop and Cassandra provides a number of advantages that have been spelled out elsewhere, so I won’t take the time to go over them here. But the question of whether Hadoop and Cassandra can work great together has been answered.
We learned a lot about combining and using and analytic data with Cassandra and Hadoop, including the fact that folks really wanted a Hive driver for Cassandra. In order to continue to improve Cassandra and contribute to the project we are committing the Hive functionality back to the Cassandra community.
With respect to Solandra, we’ve been able to demonstrate how Cassandra can benefit those wanting a more powerful underlying foundation for enterprise search in Solr.
We’re pleased with the reception that Brisk and Solandra have received and are looking forward to seeing how the community will utilize and build upon them to make them even better. Both can serve as the foundation for either other OSS projects or sellable software products.
At this time, we now consider the current versions of Brisk and Solandra to be the final releases from us in open source form.
Being that the current offerings of both Brisk and Solandra are open source, anyone can take the software and do exactly what they want to do. The current open source nature of Brisk and Solandra allows such freedom and we are happy to see others benefit from what we have provided.
We will continue to aggressively advance the Apache Cassandra project as a 100% open source project, which will serve as the foundation for our future offerings. Doing so allows us to serve and advance the community with the focus, resources, and attention that it deserves.
If you have questions or concerns, please contact us. And thanks, as always, for your support of Cassandra and DataStax.
UPDATE: Thanks for your questions/comments on this post. For answers to the main questions that have come in, please click here.