Skip to main content
Add as a preferred source on Google


IBM to Acquire AI and Data Solutions Provider DataStax

  • By John K. Waters
  • 02/28/25

IBM has announced the planned acquisition of AI and data solutions provider DataStax, in a move aimed at enhancing its watsonx portfolio and advancing generative artificial intelligence (AI) capabilities for enterprises. Financial terms of the deal were not disclosed, but the acquisition is expected to close in the second quarter of 2025, subject to regulatory approvals.

The acquisition will integrate DataStax's vector database and AI-driven data management capabilities into IBM's expanding AI ecosystem, addressing the challenge enterprises face in unlocking value from vast amounts of unstructured data.

"Businesses cannot realize the full potential of generative AI without the right infrastructure — open source tools and technologies that empower developers, harness unstructured data, and provide a strong foundation for AI applications," said Dinesh Nirmal, senior vice president of IBM Software, in a statement. "DataStax possesses deep competency in this area and shares IBM's relentless commitment to simplifying and scaling generative AI for the enterprise."

DataStax is known for AstraDB and DataStax Enterprise, its NoSQL and vector database solutions built on Apache Cassandra, as well as Langflow, an open source tool for low-code AI application development. IBM said it plans to continue supporting and developing Apache Cassandra, Langflow, and other open source initiatives such as Apache Pulsar and OpenSearch, reinforcing its commitment to open AI ecosystems.

"I've had the awesome privilege to be part of the DataStax journey for the last five-plus years and I couldn't be more excited for our next chapter," said Chet Kapoor, chairman and CEO at DataStax, in a post on LinkedIn. "We have long said that there is no AI without data, and this vision will now be amplified with IBM."

With AI adoption increasing across industries, IBM's acquisition of DataStax aims to bridge a critical gap in enterprise AI deployment. The industry analysts at McKinsey estimate that only 1% of enterprise data is currently utilized in AI models, while 70% of companies with high-performing AI initiatives still face data-related challenges. DataStax's technology is expected to enhance IBM watsonx.data, IBM's hybrid data lakehouse for AI and analytics, by enabling enterprises to manage and leverage unstructured data more effectively.

DataStax's solutions are used by major corporations, including FedEx, Capital One, The Home Depot, and Verizon. The company, founded in 2010 and headquartered in Santa Clara, California, has been instrumental in advancing database technology for AI workloads. 

About the Author

John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He's been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he's written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS.  He can be reached at [email protected].

Featured

  • circuit patterns

    Anthropic Intros Lower-Cost Claude Sonnet 5

    Anthropic has launched Claude Sonnet 5, positioning the model as its most autonomous mid-tier offering to date and a lower-cost alternative to its flagship Opus 4.8 system. The company said the model can plan multi-step tasks, operate tools such as browsers and terminals, and complete agentic work at a level that previously required larger and more expensive models.

  • abstract streams of text and data

    Anthropic Intros Invisible Watermarks to Claude-Generated Text

    Anthropic announced it is introducing machine-readable watermarks to text generated by supported Claude models as it moves to comply with European Union AI transparency rules.

  • Futuristic glowing digital book

    AI Won't Replace Teachers — But It May Be What Makes Structured Literacy Work at Scale

    Purpose-built AI systems can analyze patterns in student performance, identify specific skill gaps, and connect those gaps directly to instructional recommendations. Done well, this doesn't remove the teacher from the equation. It sharpens the teacher's ability to act.

  • lock symbol with quantum bits in dynamic motion

    Microsoft Accelerates Quantum-Safe Security Timeline

    Microsoft is speeding up its quantum-safe security timeline, noting that advances in quantum computing and new federal requirements have pushed post-quantum cryptography from a future planning issue into an immediate engineering priority.