Overview
Manage data for AI at scale
DataStax® is bringing cutting-edge capabilities—spanning Astra DB, HCD, Langflow—to watsonx®, enabling enterprises to manage real-time, unstructured and multimodal data for AI at scale. The result: Open, AI-ready infrastructure that runs anywhere—on-prem, hybrid or multi-cloud—while simplifying how enterprises power secure, governed and production-grade AI and application workloads.
Features
Key technologies
- Astra DB & HCD
- Langflow
Astra DB & Hyper-converged Database (HCD)
Astra DB and HCD enhance the NoSQL database of IBM® watsonx.data® with vector capabilities, strengthening our retrieval-augmented generation and knowledge embedding capabilities. Built for elastic scalability and predictable performance, these solutions support mission-critical workloads with near-zero latency.
Astra DB is a Forrester Leader delivering NoSQL vector search capabilities on cloud and is built on Apache Cassandra®, providing the speed, reliability and multi-model support needed for modern AI workloads—including tabular, search and graph data. This enables complex, context-sensitive searches across diverse data formats for generative AI applications.
Looking for on-prem or private cloud? Hyper-converged Database is the solution for organizations running their database resources on-premise or via private cloud. These technologies are delivered as DataStax with IBM watsonx.data Premium edition.
Langflow an open-source tool with over 100,000 GitHub stars. The tool enables developers to prototype, build and deploy retrieval-augmented generation and multi-agent AI applications through an intuitive low-code interface.
Langflow integrates flexibly with IBM® watsonx Orchestrate® as middleware to streamline AI application development. With trusted infrastructure, composable tooling and open-source innovation, IBM and DataStax provide a robust foundation to help enterprises unlock deeper insights from unstructured data—securely and at scale.
Built in Python and designed to work across models, APIs and databases, Langflow helps teams streamline generative AI development by reducing complexity and supporting a frictionless path from prototype to production.
Use cases
Built for real‑world scenarios
Langflow has earned over 100,000 stars on GitHub, reflecting its rapid adoption and ability to simplify generative AI development at scale.
Tens of thousands of developers use Langflow to reduce complexity and speed up every stage of the generative AI pipeline from orchestration to deployment.
Astra DB delivers real-time performance with near-zero latency, and is built for high-speed vector search and AI workloads.
Automate ingestion, enrichment and retrieval of unstructured data to reduce friction and accelerate the deployment and scaling of AI workloads and enterprise applications.
Simply secure data access and governance with enterprise-grade tooling, built on trusted infrastructure and open-source innovation, seamlessly integrated with watsonx to deliver built-in encryption, access controls and streamlined orchestration of unstructured data.
Lower the total cost of ownership and simplify AI operations by automating unstructured data management, helping reduce overall cloud database costs.
Complementary with watsonx, scale and deploy reliable AI workloads across any cloud or on-premises environment by using open source, low-code tooling for the ultimate speed and flexibility for modern enterprise applications.
Pricing
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