Vector-enabled NoSQL data
Astra DB and HCD extend watsonx.data NoSQL capabilities with vector functionality for retrieval-augmented generation and knowledge embedding workflows.
IBM DataStax brings Astra DB, Hyper-converged Database (HCD) and Langflow into the watsonx portfolio to help enterprises manage real-time, unstructured and multimodal data for AI applications. It supports AI workloads across on-premises, hybrid and multicloud environments.
IBM DataStax combines DataStax technologies with IBM watsonx to help enterprises manage real-time, unstructured and multimodal data for AI applications. The offering includes Astra DB, Hyper-converged Database (HCD) and Langflow.
Astra DB and HCD add vector capabilities to the NoSQL functionality of watsonx.data, supporting retrieval-augmented generation and knowledge embedding workflows. Langflow provides a low-code environment for building retrieval-augmented generation and multi-agent applications. The technologies are positioned for deployment across on-premises, private-cloud, hybrid and multicloud environments, depending on the component and use case.
Astra DB and HCD extend watsonx.data NoSQL capabilities with vector functionality for retrieval-augmented generation and knowledge embedding workflows.
Astra DB is built on Apache Cassandra and supports multiple data forms and operations, including tabular, search and graph data for AI applications.
Hyper-converged Database is positioned for organizations that need to run database resources on-premises or in a private cloud.
Langflow provides an open-source interface for prototyping, building and deploying retrieval-augmented generation and multi-agent applications.
Built in Python, Langflow is designed to work across models, APIs and databases, allowing teams to compose application workflows from different components.
The IBM product page describes built-in encryption, access controls and governance capabilities for securing and managing access to unstructured data.
Teams can combine Langflow application orchestration with Astra DB or HCD vector capabilities to build AI experiences grounded in enterprise data.
Developers can use Langflow's low-code interface to prototype and deploy multi-agent applications before integrating them into broader enterprise workflows.
Organizations can use the watsonx.data and Astra DB combination for applications that depend on current operational data, such as personalization, payments, recommendations and order activity.
Real-time ingestion and low-latency access can support fleet tracking, inventory visibility, shipment updates, device events and other operational signals.
Organizations with on-premises or private-cloud requirements can evaluate HCD alongside watsonx capabilities for keeping database resources in controlled environments.
The IBM product page identifies Astra DB, Hyper-converged Database (HCD) and Langflow as the main DataStax technologies being brought into the watsonx portfolio.
Astra DB is a Cassandra-based NoSQL database with vector capabilities. IBM describes it as supporting tabular, search and graph data operations, as well as retrieval-augmented generation and other AI workloads.
Langflow is an open-source, low-code tool for prototyping, building and deploying retrieval-augmented generation and multi-agent AI applications. It is built in Python and works across models, APIs and databases.
The product positioning supports on-premises, hybrid and multicloud deployment. HCD is specifically described as an option for organizations running database resources on-premises or in a private cloud.
The related watsonx.data pricing page lists pay-per-use and subscription options, along with a free trial and purchase paths through IBM Cloud and AWS. The available evidence does not specify a separate price for every IBM DataStax component.
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