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Informations pour les développeurs et articles pratiques de nos experts pour inspirer et dynamiser votre expérience de recherche
Elasticsearch open inference API adds support for Azure OpenAI embeddings
Elasticsearch open inference API adds support for Azure OpenAI embeddings to be stored in the world's most downloaded vector database.
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.
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.
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.
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.
Building Elastic Cloud Serverless
Explore the architecture of Elastic Cloud Serverless and key design and scalability decisions we made along the way of building it.
Search relevance tuning: Balancing keyword and semantic search
This blog offers practical strategies for tuning search relevance that can be complementary to semantic search.
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.
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.
How to detect which index template Elasticsearch will use before an index creation
Learn about Elasticsearch index templates and how to detect which index template Elasticsearch will use before creating the index itself.
RAG & RBAC integration: Protect data and boost AI capabilities
Discover how Retrieval Augmented Generation (RAG) & Role-Based Access Control (RBAC) integrate to protect data and boost AI capabilities.