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Elasticsearch is a distributed search and analytics engine built on Apache Lucene. It lets you store, search, and analyze large volumes of data in near real time — powering full-text search, vector similarity search, log analytics, and AI-augmented applications.

Quickstart

Run Elasticsearch locally and make your first search query in minutes.

Installation

Install and configure Elasticsearch on your own infrastructure.

Core Concepts

Learn about indices, shards, documents, mappings, and cluster architecture.

API Reference

Explore the full REST API — document, search, index, and cluster operations.

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What you can build

Full-Text Search

Powerful Query DSL with relevance scoring, highlighting, and suggestions.

Vector Search

Semantic and k-nearest neighbor search with dense and sparse vectors.

ES|QL Analytics

Piped query language for filtering, aggregating, and transforming data.

Aggregations

Bucket, metric, and pipeline aggregations for real-time analytics.

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Get started

1

Run Elasticsearch locally

Use the start-local script to spin up Elasticsearch and Kibana with Docker:
curl -fsSL https://elastic.co/start-local | sh
2

Index your first document

curl -X POST "localhost:9200/my-index/_doc" \
  -H "Content-Type: application/json" \
  -d '{"title": "Hello Elasticsearch", "body": "Distributed search at scale"}'
3

Search your data

curl "localhost:9200/my-index/_search?q=hello"
4

Explore the docs

Dive into Core Concepts, Indexing & Data, and the API Reference.

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