Category: Vector Database

Articles tagged Vector Database

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Elasticsearch open inference API adds Azure AI Studio support

Elasticsearch open inference API now supports Azure AI Studio. Learn how to use Azure AI Studio capabilities with Elasticsearch in this blog.

Mark Hoy

Elasticsearch delivers performance increase for users running the Elastic Search AI Platform on Arm-based architectures

Benchmarking in preview provides Elasticsearch up to 37% better performance on Azure Cobalt 100 Arm-based VMs.

Yuvraj Gupta

Elastic Cloud adds Elasticsearch Vector Database optimized profile to Microsoft Azure

Elasticsearch added a new vector search optimized profile to Elastic Cloud on Microsoft Azure. Get started and learn how to use it here.

Serena Chou

How to choose between exact and approximate kNN search in Elasticsearch

Learn more about exact and approximate kNN search in Elasticsearch, and when to use each one.

Carlos Delgado

Search relevance tuning: Balancing keyword and semantic search

This blog offers practical strategies for tuning search relevance that can be complementary to semantic search.

Kathleen DeRusso

Vector similarity measures and scoring

Explore vector similarity measures​ and scoring in Elasticsearch, including L1 & L2 distance, cosine similarity, dot product similarity and max inner product similarity.

Valentin Crettaz

Retrieval of originating information in multi-vector documents

Learn about multi-vector documents in Elasticsearch, their use cases, and how to link original context to a multi-vector document.

Gilad Gal

Red Hat & Elastic: Red Hat OpenShift AI integration with Elasticsearch

Red Hat OpenShift users can now implement Elasticsearch for vector search & RAG applications via the Red Hat Ecosystem Catalog. Explore this integration here.

Aditya Tripathi

Making Elasticsearch and Lucene the best vector database: up to 8x faster and 32x efficient

Discover the recent enhancements and optimizations that notably improve vector search performance in Elasticsearch & Lucene vector database.

Mayya Sharipova

Scalar quantization optimized for vector databases

Optimizing scalar quantization for the vector database use case allows us to achieve significantly better performance for the same retrieval quality at high compression ratios.

Thomas Veasey

Elastic Cloud adds Elasticsearch Vector Database optimized instance to Google Cloud

Elasticsearch's vector search optimized profile for GCP is available. Learn more about it and how to use it in this blog.

Serena Chou

Simplifying kNN search

Elastic's kNN search has evolved. This blog explains the simplification of kNN search, where k and num_candidates are now optional.

Panagiotis Bailis

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