# Source: https://docs.embedchain.ai/components/vector-databases/elasticsearch.md

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

# Elasticsearch

Install related dependencies using the following command:

```bash  theme={null}
pip install --upgrade 'embedchain[elasticsearch]'
```

<Note>
  You can configure the Elasticsearch connection by providing either `es_url` or `cloud_id`. If you are using the Elasticsearch Service on Elastic Cloud, you can find the `cloud_id` on the [Elastic Cloud dashboard](https://cloud.elastic.co/deployments).
</Note>

You can authorize the connection to Elasticsearch by providing either `basic_auth`, `api_key`, or `bearer_auth`.

<CodeGroup>
  ```python main.py theme={null}
  from embedchain import App

  # load elasticsearch configuration from yaml file
  app = App.from_config(config_path="config.yaml")
  ```

  ```yaml config.yaml theme={null}
  vectordb:
    provider: elasticsearch
    config:
      collection_name: 'es-index'
      cloud_id: 'deployment-name:xxxx'
      basic_auth:
        - elastic
        - <your_password>
      verify_certs: false
  ```
</CodeGroup>

<Snippet file="missing-vector-db-tip.mdx" />