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According to a new press release, DataStax has announced the upcoming release of its Hyper-Converged Data Platform (HCDP) and DataStax Enterprise (DSE) 6.9, both designed to empower enterprises with generative AI and vector search capabilities for their self-managed data workloads. HCDP is tailored for modern data centers and Hyper-Converged Infrastructure (HCI), providing support for a wide range of data workloads and AI systems. It aims to help enterprise operators and architects leverage data center modernization investments to reduce costs and operational overhead, while integrating advanced AI-enabled data systems.
The HCDP integrates OpenSearch for enterprise search and Apache Pulsar for high-performance vector search, enabling rapid and flexible data retrieval necessary for generative AI and knowledge applications. This integration supports retrieval-augmented generation (RAG) knowledge retrieval, essential for producing AI-driven insights. DataStax’s adoption of OpenSearch as part of HCDP fosters a community-driven approach, enhancing the capabilities for AI-powered services and applications. The platform also features Hyper-Converged Streaming (HCS) with Apache Pulsar, which offers native inline data processing and embedding, improving data communications and allowing faster responses and better generative AI experiences.
DataStax Enterprise 6.9 introduces generative AI capabilities to existing on-premises Cassandra and DSE workloads, enhancing operational efficiency and reducing total cost of ownership. The new version includes a vector add-on for enhanced search capabilities and DataStax Mission Control for simplified cloud-native operations and observability on Kubernetes. This upgrade supports a seamless transition for enterprises looking to modernize their technology stacks and optimize their data systems. With DSE 6.9, DataStax continues to deliver advanced tools for real-time data services, making it easier for businesses, like those in the financial sector, to enhance productivity and customer engagement while maintaining system efficiency.