Blogs

Developer insights and practical how-to articles from our experts to inspire and empower your search experience.

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How do Elasticsearch snapshots work?

During our instructor-led “Elasticsearch Engineer” training, one of the most common questions we get while teaching about snapshots is “what is the incremental nature of snapshots?” This blog post will cover that topic in detail.

Lutf ur Rehman

Chunking large documents via ingest pipelines plus nested vectors equals easy passage search

Learn how to chunk large documents using ingest pipelines and nested vectors in Elasticsearch for easy passage search in vector search.

Michael Heldebrant

Retrieval Augmented Generation (RAG)

Learn about Retrieval Augmented Generation (RAG) and how it can help improve the quality of an LLM's generated responses by providing relevant source knowledge as context.

Joe McElroy

Understanding scalar quantization in Lucene

Explore how Elastic introduced scalar quantization into Lucene, including automatic byte quantization, quantization per segment & performance insights.

Benjamin Trent

Implementing image search: vector search via image processing in Elasticsearch

Learn how to implement image search with an example. This blog covers how to use vector search through image processing in Elasticsearch.

Alex Salgado

A conversational search experience for retail: Elasticsearch Relevance Engine with Google Cloud’s generative AI

This blog presents a new search experience for retailers using generative AI with Vertex AI and Elasticsearch.

Valerio Arvizzigno

Using hybrid search for gopher hunting with Elasticsearch and Go

Learn how to achieve hybrid search by combining keyword and vector search using Elasticsearch and the Elasticsearch Go client.

Carly Richmond

Perform vector search in Elasticsearch with the Elasticsearch Go client

Learn how to perform vector search in Elasticsearch using the Elasticsearch Go client through a practical example.

Carly Richmond

Perform text queries with the Elasticsearch Go client

Learn how to perform traditional text queries in Elasticsearch using the Elasticsearch Go client through a practical example.

Carly Richmond

Elasticsearch as a GenAI caching layer

Explore how integrating Elasticsearch as a caching layer optimizes Generative AI performance by reducing token costs and response times, demonstrated through real-world testing and practical examples.

Jeff Vestal

Scalar quantization 101

Understand what scalar quantization is, how it works and its benefits. This guide also covers the math behind quantization and examples.

Benjamin Trent

How to Use Amazon Bedrock with Elasticsearch and Langchain

Learn to split workplace documents into passages, transform these passages into embeddings in Elasticsearch and integrate Amazon Bedrock LLM.

Yan Savitski