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Free and Open, Distributed, RESTful Search Engine

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= Elasticsearch

== A Distributed RESTful Search Engine


Elasticsearch is a distributed RESTful search engine built for the cloud. Features include:

  • Distributed and Highly Available Search Engine. ** Each index is fully sharded with a configurable number of shards. ** Each shard can have one or more replicas. ** Read / Search operations performed on any of the replica shards.
  • Multi-tenant. ** Support for more than one index. ** Index level configuration (number of shards, index storage, etc.).
  • Various set of APIs ** HTTP RESTful API ** All APIs perform automatic node operation rerouting.
  • Document oriented ** No need for upfront schema definition. ** Schema can be defined for customization of the indexing process.
  • Reliable, Asynchronous Write Behind for long term persistency.
  • Near real-time search.
  • Built on top of Apache Lucene ** Each shard is a fully functional Lucene index ** All the power of Lucene easily exposed through simple configuration and plugins.
  • Per operation consistency ** Single document-level operations are atomic, consistent, isolated, and durable.

== Getting Started

First of all, DON'T PANIC. It will take 5 minutes to get the gist of what Elasticsearch is all about.

=== Installation

  •[Download] and unpack the Elasticsearch official distribution.
  • Run
    on Linux or macOS. Run
    on Windows.
  • Run
    curl -X GET http://localhost:9200/
    to verify Elasticsearch is running.

=== Indexing

First, index some sample JSON documents. The first request automatically creates the


curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d ' { "@timestamp": "2099-11-15T13:12:00", "message": "GET /search HTTP/1.1 200 1070000", "user": { "id": "kimchy" } }'

curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d ' { "@timestamp": "2099-11-15T14:12:12", "message": "GET /search HTTP/1.1 200 1070000", "user": { "id": "elkbee" } }'

curl -X POST 'http://localhost:9200/my-index-000001/_doc?pretty' -H 'Content-Type: application/json' -d ' { "@timestamp": "2099-11-15T01:46:38", "message": "GET /search HTTP/1.1 200 1070000", "user": { "id": "elkbee" }


=== Search

Next, use a search request to find any documents with a

curl -X GET 'http://localhost:9200/my-index-000001/_search?'

Instead of a query string, you can use Elasticsearch's[Query DSL] in the request body.

curl -X GET 'http://localhost:9200/my-index-000001/_search?pretty=true' -H 'Content-Type: application/json' -d ' { "query" : { "match" : { "": "kimchy" } }


You can also retrieve all documents in


curl -X GET 'http://localhost:9200/my-index-000001/search?pretty=true' -H 'Content-Type: application/json' -d ' { "query" : { "matchall" : {} }


During indexing, Elasticsearch automatically mapped the

field as a date. This lets you run a range search.

curl -X GET 'http://localhost:9200/my-index-000001/_search?pretty=true' -H 'Content-Type: application/json' -d ' { "query" : { "range" : { "@timestamp": { "from": "2099-11-15T13:00:00", "to": "2099-11-15T14:00:00" } } }


=== Multiple indices

Elasticsearch supports multiple indices. The previous examples used an index called

. You can create another index,
, to store additional data when
reaches a certain age or size. You can also use separate indices to store different types of data.

You can configure each index differently. The following request creates

with two primary shards rather than the default of one. This may be helpful for larger indices.

curl -X PUT 'http://localhost:9200/my-index-000002?pretty' -H 'Content-Type: application/json' -d ' { "settings" : { "index.numberofshards" : 2 }


You can then add a document to


curl -X POST 'http://localhost:9200/my-index-000002/_doc?pretty' -H 'Content-Type: application/json' -d ' { "@timestamp": "2099-11-16T13:12:00", "message": "GET /search HTTP/1.1 200 1070000", "user": { "id": "kimchy" }


You can search and perform other operations on multiple indices with a single request. The following request searches


curl -X GET 'http://localhost:9200/my-index-000001,my-index-000002/search?pretty=true' -H 'Content-Type: application/json' -d ' { "query" : { "matchall" : {} }


You can omit the index from the request path to search all indices.

curl -X GET 'http://localhost:9200/search?pretty=true' -H 'Content-Type: application/json' -d ' { "query" : { "matchall" : {} }


=== Distributed, highly available

Let's face it; things will fail...

Elasticsearch is a highly available and distributed search engine. Each index is broken down into shards, and each shard can have one or more replicas. By default, an index is created with 1 shard and 1 replica per shard (1/1). Many topologies can be used, including 1/10 (improve search performance) or 20/1 (improve indexing performance, with search executed in a MapReduce fashion across shards).

To play with the distributed nature of Elasticsearch, bring more nodes up and shut down nodes. The system will continue to serve requests (ensure you use the correct HTTP port) with the latest data indexed.

=== Where to go from here?

We have just covered a tiny portion of what Elasticsearch is all about. For more information, please refer to the[] website. General questions can be asked on the[Elastic Forum] or[on Slack]. The Elasticsearch GitHub repository is reserved for bug reports and feature requests only.

=== Building from source

Elasticsearch uses[Gradle] for its build system.

To build a distribution for your local OS and print its output location upon

completion, run:

./gradlew localDistro

To build a distribution for another platform, run the related command:

./gradlew :distribution:archives:linux-tar:assemble ./gradlew :distribution:archives:darwin-tar:assemble

./gradlew :distribution:archives:windows-zip:assemble

To build distributions for all supported platforms, run:

./gradlew assemble

Finished distributions are output to


See the xref:TESTING.asciidoc[TESTING] for more information about running the Elasticsearch test suite.

=== Upgrading from older Elasticsearch versions

To ensure a smooth upgrade process from earlier versions of Elasticsearch, please see our[upgrade documentation] for more details on the upgrade process.

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