DataStax Astra

Founded by Jonathan Ellis in 2010

Store unstructured vector data and build retrieval-augmented generation applications at scale

Pricing model

Paid

Rating

★ Positive

Time to value

Immediate

You can use DataStax to manage vector data and build production-ready generative AI applications. It combines Astra DB, a cloud database built on Apache Cassandra, with Langflow for visual workflow development. Developers can ingest unstructured documents, run vector searches with low latency, and connect data directly to large language models. The system supports retrieval-augmented generation pipelines, multi-agent architectures, and hybrid cloud deployments. Teams can also manage security controls, access governance policies, and scale workloads across on-premise hardware and multiple public clouds without operational friction.

What DataStax Astra does

Store vector embeddings generated by machine learning modelsCreate multi-agent AI pipelines using drag-and-drop componentsExecute semantic similarity queries against unstructured textDeploy Cassandra database clusters across multi-cloud environmentsConfigure role-based access controls and encryption for AI datasetsConnect external APIs and foundation models to Langflow workflowsSynchronize real-time transactional data with AI retrieval endpointsVector search built on Apache Cassandra NoSQL architectureVisual RAG and multi-agent workflow development with LangflowHybrid deployment across on-premises, private cloud, and public cloudsNear-zero latency query execution for real-time AI workloadsMulti-model support for tabular, search, and graph data formatsAutomated unstructured data ingestion, enrichment, and retrievalNative integration with IBM watsonx governance and orchestration tools