IBM to Acquire DataStax, Deepening watsonx Capabilities and Addressing Generative AI Data Needs for the Enterprise
Planned acquisition furthers

The acquisition also builds on
Harnessing unstructured data for the enterprise
Businesses are struggling to harness valuable, unstructured data from across their business, which is critical for powering generative AI. Without tools to properly ingest and manage this untapped data, costly generative AI projects will fail to deliver their full potential. Even 70% of companies with high-performing generative AI initiatives experience data-related difficulties, according to McKinsey, and it is estimated that just one percent of enterprise data is represented in today's AI models.
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AstraDB
andDataStax Enterpriseprovide NoSQL and vector database capabilities powered by Apache Cassandra®, enabling production-ready generative AI applications for the enterprise. AstraDB will enhance the existing vector capabilities of
IBM watsonx.data,IBM's hybrid, open data lakehouse for AI and analytics. Thousands of organizations use Apache Cassandra®, including some of the biggest names in software, retail, finance, and ecommerce. Apache Cassandra® provides scalability, availability, fault tolerance, high performance, and multi-data-center and hybrid cloud support. And increasingly, Apache Cassandra® users are leveraging the database for AI workloads. In this context,DataStax brings together a mature datastore with vector and graphRAG capabilities – a critical combination for harnessing unstructured data for generative AI -
Langflow
is a low-code, open-source app builder for RAG and multi-agent AI applications. It is Python-based and model-, API-, and database-agnostic. Langflow adds additional flexible middleware capabilities to
IBM watsonx.ai, the integrated, end-to-end AI development studio for building generative AI applications
"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," says
"Enterprises want to deliver production AI fast, but are still struggling to unlock the value in their data to power AI applications and agents," says
Financial details of the transaction were not disclosed. The acquisition is expected to close in the second quarter of 2025, subject to customary closing conditions and regulatory approvals.
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