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Attention Database Architects and Application Developers: Hadoop has Grown Up!

April 11, 2014
Hadoop and the Relational Database hadoop is maturing

There’s an elephant in the room and for once, everyone is talking about it. No longer just an interesting data management technology for batch processing, Hadoop is maturing into the distributed infrastructure for the next generation of RDBMSs (Relational Database Management Systems) – thanks to the efforts of the Apache community, the organizations behind the various Hadoop distributions and those companies building on top of Hadoop, such as Splice Machine.

In the early years of Hadoop, many database architects or application developers looking to manage extremely large data sets were deciding between a NoSQL solution and an early adopter’s version of Hadoop. Choosing the NoSQL solution meant giving up full SQL support in order to achieve scalability on commodity hardware. Choosing the early version of Hadoop meant a great place to store massive amounts of data and perform batch analytics jobs, but no ability to power real-time applications or analytics. But Hadoop has grown up, and with it, everything has changed.

2014 is a watershed year for Hadoop, as it moves well beyond its heritage as a batch processing platform. The only Hadoop RDBMS, Splice Machine can be a very compelling alternative to traditional RDBMSs like Oracle or MySQL by cost-effectively scaling out on commodity hardware. Our database platform includes the features that made RDBMS so popular for so long – such as ACID transactions and standard SQL. App developers can now get the best of both worlds: the ability to scale real-time applications with commodity hardware without the application rewrites that NoSQL databases require.

If you’re an app developer, Hadoop is here and it’s not going away. It’s going to be the big elephant in the room for every other database system. If you’ve got questions about how real-time, transactional Hadoop can power your applications, reach out to Splice Machine through our website, LinkedIn or Twitter. We’re excited to share our vision for a new generation of Hadoop-based apps.