IBM to Acquire DataStax

IBM is acquiring DataStax - creator of DataStax Enterprise, the Enterprise distribution of Apache Cassandra . DataStax is one of a sextet of database companies founded in the late 2000s - early 2010s that collectively raised a few billion dollars in venture funding and built large Enterprise businesses while staying private - with one notable exception. For reference, the other five I'm thinking of are Redis (founded 2011, raised $357M), Couchbase (2009, $251M), MongoDB (2007, $311M), SingleStore (2011, $464M) and Cockroach Labs (2015, $633M).

Founded in 2010, DataStax had raised a total of $343M, including a $115 million round in June 2022 led by Goldman Sachs Asset Management . Other backers include Crosslink Capital , Meritech Capital and Scale Venture Partners .

DataStax has established itself as a key player in the NoSQL database market with its flagship products AstraDB and DataStax Enterprise. Its client roster includes major enterprises including FedEx, Capital One, Verizon, The Home Depot, and Audi.

The deal brings DataStax's vector database capabilities and Langflow , an open-source AI application development tool with over 49,000 GitHub stars, under IBM's umbrella. These technologies will integrate with IBM's watsonx AI platform to enhance its enterprise AI offerings.

Chet Kapoor , Chairman and CEO of DataStax , wrote in a company blog post that the acquisition will help enterprises leverage "knowledge locked in their enterprise data estate to power their AI agents and large language models."

As is typical in these kinds of deals, the companies have pledged continued support for Apache Cassandra. Patrick McFadin, Principal Technical Strategist at DataStax and a Cassandra committer, emphasized that the acquisition signals "a strategic bet on the future of Cassandra."

Last week was for large rounds in AI Inferencing (Baseten and Together AI). This week is for database companies I guess. MongoDB announced its intent to acquire Voyage AI for $220M a couple of days ago. It is great to see Enterprise Gen AI drive a wave of consolidation in the data layer. More to come, I bet.

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