DataStax Enterprise 3.1: NoSQL; Yes, CQL.

DataStax Enterprise gets the Cassandra Query Language. And DataStax gets $45 million in new funding.
Written by Andrew Brust, Contributor

DataStax, the major commercial entity behind the Apache Cassandra wide column store NoSQL database, is today announcing version 3.1 of its DataStax Enterprise distribution.  

CQL, more data, better search
This release brings the Cassandra Query Language ("CQL") -- the SQL-like query language for Cassandra -- to DataStax Enterprise.  DataStax will also supply Java and .NET drivers for the CQL interface.

Other features include support for a 10-fold increase in data per node, and integration with Apache Solr 4.3, bringing 60 new search-related features.  Support for virtual nodes ("vnodes") and new tracing features have been added as well.

While the prior release of DataStax Enterprise brought security improvements, including grant and revoke of object permissions and Kerberos authentication, the 3.1 release focuses on programmability.  Together, these two releases address previous gaps in Cassandra's enterprise credibility.  

Can't stand the suspense?
The next release of DataStax Enterprise will be based on Cassandra 2.0 and will add even more enterprise features.  Customers eager to test these capabilities out now may do so with the new 2.0 release of DataStax Community Edition, which includes Compare and Set (CAS) "lightweight" transactions, triggers, improved compaction, eager retries, and database cursors in the CQL environment.

Show me the money
DataStax is also announcing a new $45 million series D round of funding, led by Scale Venture Partners, with participation from existing investors Lightspeed Venture Partners, Crosslink Capital and Meritech Capital Partners, and new investors DFJ Growth and Next World Capital.  The new funding will be used for a combination of product development and geographic expansion.

Between new features and new funding, DataStax is clearly aiming to take market share from Oracle, Microsoft SQL Server and IBM DB2, among others.  Will the combination of its massive scale-out architecture and buttoned-down enterprise features do the trick, or will DataStax merely make a dent?  The answer will come when revenue replaces funding as the topic of conversation.

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