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An OpenSearch plugin that expands its capabilities with the custom `knn_vector` data type, enabling storage of embeddings and providing methods for k-NN similarity searches, including Approximate k-NN, Script Score k-NN, and Painless extensions.
Amazon OpenSearch's k-NN plugin enables scalable, efficient vector search using ANN algorithms (IVF, HNSW) directly within a managed OpenSearch cluster. It is directly relevant for building, querying, and scaling vector databases on AWS.
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An on-demand serverless configuration for OpenSearch Service that simplifies the operational complexities of managing OpenSearch domains, integrated with Knowledge Bases for Amazon Bedrock to support generative AI applications.
The k-NN plugin enhances OpenSearch by introducing a custom knn_vector data type. This enables the storage of vector embeddings and provides robust methods for performing k-nearest neighbors (k-NN) similarity searches.
knn_vector data type into OpenSearch.Pricing information is not available.
License information is available, but specific details are not provided in the content. As an OpenSearch project plugin, it is typically open-source.