Blog
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Efficient filtering in OpenSearch vector engine
With the release of OpenSearch 2.9, we introduced efficient filtering, or “filter-while-search,” functionality for queries using the Facebook AI Similarity Search (Faiss) engine. This update overcomes the previous limitations of pre-filtering and post-filtering in the OpenSearch vector engine. In the OpenSearch 2.10 release, we added support for filtering using the inverted file (IVF) algorithm and further improved the overall performance...
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Introducing concurrent segment search in OpenSearch
OpenSearch is a scalable, flexible, and extensible open-source search and analytics engine. It is built on top of Apache Lucene and uses its powerful capabilities to ingest user data and serve search requests with latency in milliseconds.
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Get started with OpenSearch 2.11
OpenSearch 2.11 is now available, with exciting new capabilities for observability applications, an expanded selection of search tools, enhancements to data durability, and more, along with new experimental functionality to explore. For a complete view of what’s new in this release, see the release notes, and you can give OpenSearch Dashboards a try on OpenSearch Playground.
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Announcing Data Prepper 2.5.0
Data Prepper 2.5.0 is now available for download. This release includes a new OpenSearch source, new dissect and translate processors, and additions to the existing key-value processor.
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Byte-quantized vectors in OpenSearch
In OpenSearch k-NN plugin when we index and query vectors of type float, each vector element occupies 4 bytes. This is getting expensive in terms of memory and storage, especially for large-scale use cases. Starting with the OpenSearch 2.9 release, using the new byte vector feature we can reduce memory and storage requirements, significant reduction in query latencies with a...
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