The latest release of Aerospike Vector Search features a self-healing hierarchical navigable small world (HNSW) index, enabling scale-out data ingestion and uninterrupted query performance.
With the new Python client and sample apps, developers can quickly deploy vector use cases, integrating semantic search into AI applications using Aerospike's architecture.
Aerospike's multi-model database allows for document, key-value, graph, and vector search, enhancing capabilities for AI applications in areas like fraud prevention and recommendations.
The integration with frameworks and cloud partners through Aerospike's LangChain extension accelerates the development of retrieval-augmented generation applications, making it easier for developers.
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