> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mezmo.com/llms.txt
> Use this file to discover all available pages before exploring further.

# ElasticSearch

> Send indexed log data to an ElasticSearch destination, with options for authentication strategy, compression, endpoints, and indices.

## Description

Typically you would use ElasticSearch to store and analyze large amounts of data which are of different structures and formats. An ElasticSearch cluster is composed of **Clusters**, **Indices**, **Nodes**, and **Shards** that help organize and manage how your data is stored. The data can then be efficiently and powerfully searched and analyzed.

ElasticSearch is usually used as a Pipeline destination when your log data needs to be indexed for searching. By setting up a Pipeline for your ElasticSearch data, you can use Pipeline Processors like [Dedupe](/telemetry-pipelines/dedupe-processor) and [Remove Fields](/telemetry-pipelines/drop-fields-processor) to clean data or drop it if it’s not valuable before sending it to ElasticSearch.

## Configuration Options

| Option | Description |
| - | - |
| End-to-End Acknowledgement | Enable this option to receive verification that log data is being received by ElasticSearch. |
| Compression | Compression type to apply to your log data. |
| Strategy | The authentication strategy of your ElasticSearch destination, with options for **Basic** and **AWS**. |
| Endpoints | The full URLs of the ElasticSearch destinations. |
| Pipeline | The name of the ElasticSearch ingest pipeline to use. |
| Custom Index | The index name or pattern of the ElasticSearch destination. |