Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
Playground: Experiment with RAG applications with Elasticsearch in minutes
Learn about Elastic's Playground and how to use it to experiment with RAG applications using Elasticsearch.
Elasticsearch vs. OpenSearch: Vector Search Performance Comparison
Elasticsearch is out-of-the-box 2x–12x faster than OpenSearch for vector search
Elasticsearch new semantic_text mapping: Simplifying semantic search
Learn how to use the new semantic_text field type and semantic query for simplifying semantic search in Elasticsearch.
Elasticsearch data ingestion - What's the best data ingestion tool for the job?
Discover the different ways you can ingest data in Elasticsearch. Explore data ingestion tools like Logstash, Client APIs and Elastic Native Connectors + the Elastic Connector Framework.
Building RAG with Llama 3 open-source and Elastic
Learn how to build a RAG system with Llama3 open source and Elastic. This blog provides practical examples of RAG using Llama3 as an LLM.
Enhancing recommendations with geo-semantic search in Elasticsearch
Explore Elasticsearch's hybrid geo-semantic search capabilities and learn how to integrate geographical & semantic search to enhance recommendations.
RAG pipelines in production: Operationalize your GenAI project
In this blog, we discuss the necessary considerations for running Retrieval Augmented Generation (RAG) pipelines in production.
Simplifying data lifecycle management for data streams
Elasticsearch data streams can now be managed by a data stream property called lifecycle. Learn to set up and update a data stream lifecycle here.
Designing for large scale vector search with Elasticsearch
Explore the cost, performance and benchmarking for running large-scale vector search in Elasticsearch, with a focus on high-fidelity dense vector search.
Intelligent RAG data chunking: Fetch surrounding chunks
Learn about data chunking in RAG and explore fetch surrounding chunking, a pattern in RAG that uses chunking and Elasticsearch to refine LLM responses.
LangChain-Elasticsearch vector database integration and retrievers for RAG
Explore the LangChain and Elasticsearch integration and how it enables you to easily build RAG solutions and leverage retrievers.
