IBM DataStax

Unlock enterprise data for AI - unstructured, real-time, and production-ready.

Most enterprise data is unstructured – documents, text, images, and other formats that traditional databases cannot handle effectively. DataStax, an IBM company, provides the infrastructure to make that data accessible to AI: vector search, real-time retrieval, and low-code development tooling that reduces the complexity of building and scaling generative AI applications in production. Integrated natively with IBM watsonx, DataStax sits at the heart of Dot Group’s AI platform architecture, the layer that gives AI applications access to the full breadth of enterprise data, not just the structured fraction.

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Vector search and unstructured data at scale

Astra DB delivers NoSQL vector search capabilities built on Apache Cassandra – providing the speed, reliability, and multi-model support that generative AI workloads require, including tabular, search, and graph data. Near-zero latency and elastic scalability support mission-critical AI applications at scale. For organisations running on-premises or in private cloud, the Hyper-converged Database (HCD) brings the same capabilities outside the public cloud. Both are delivered as DataStax with IBM watsonx.data Premium edition.

Find out more on the IBM website: IBM DataStax >

The operational AI data layer

AI applications need more than stored data, they need data that reflects what is happening now. DataStax provides the real-time retrieval and vector search capabilities that allow AI systems to access current, contextualised information at the moment of inference, rather than reasoning from snapshots that are already out of date. Combined with SingleStore for unified transactional and analytical performance, DataStax completes the operational AI data layer that underpins Dot Group’s AI platform architecture, giving AI applications access to the right data, in the right format, at the right moment.

From prototype to production with Langflow

Langflow is an open-source, low-code tool for building retrieval-augmented generation and multi-agent AI applications, enabling developers to prototype, build, and deploy generative AI workflows through an intuitive visual interface. Built in Python and designed to work across models, APIs, and databases, Langflow integrates with IBM watsonx Orchestrate as middleware, streamlining the path from development to production-grade AI applications. With over 100,000 GitHub stars and tens of thousands of active developers, it has become a foundational tool for enterprise generative AI development.

Deploy anywhere, govern everything

DataStax runs across any cloud or on-premises environment, complementing the watsonx platform’s hybrid and multi-cloud deployment model. Enterprise-grade encryption, access controls, and governance tooling are built in – simplifying how organisations secure and manage unstructured data at scale without adding operational complexity. Works alongside watsonx.data intelligence for cataloguing and lineage, and watsonx.governance for enterprise AI risk and compliance.

DataStax in action

DataStax is the unstructured data and vector search layer within Dot Group’s Activate AI platform architecture – working alongside SingleStore for operational and analytical workloads, and watsonx Orchestrate for agent orchestration. Together they form the AI-ready data platform that gives enterprises the infrastructure to move AI from experimentation into production.

See how DataStax fits into our Activate AI approach >