> ## Documentation Index
> Fetch the complete documentation index at: https://private-7c7dfe99-fix-nav-issues.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> This engine provides a read-only integration with existing Delta Lake tables in Amazon S3.

# DeltaLake table engine

This engine provides an integration with existing [Delta Lake](https://github.com/delta-io/delta) tables in S3, GCP and Azure storage and supports both reads and writes (from v25.10).

<h2 id="create-table">
  Create a DeltaLake table
</h2>

To create a DeltaLake table it must already exist in S3, GCP or Azure storage. The commands below do not take DDL parameters to create a new table.

<Tabs>
  <Tab title="S3">
    **Syntax**

    ```sql theme={null}
    CREATE TABLE table_name
    ENGINE = DeltaLake(url, [aws_access_key_id, aws_secret_access_key,] [extra_credentials])
    ```

    **Engine parameters**

    * `url` — Bucket url with path to the existing Delta Lake table.
    * `aws_access_key_id`, `aws_secret_access_key` - Long-term credentials for the [AWS](https://aws.amazon.com/) account user.  You can use these to authenticate your requests. Parameter is optional. If credentials are not specified, they are used from the configuration file.
    * `extra_credentials` - Optional. Used to pass a `role_arn` for role-based access in ClickHouse Cloud. See [Secure S3](/products/cloud/guides/data-sources/accessing-s3-data-securely) for configuration steps.

    Engine parameters can be specified using [Named Collections](/concepts/features/configuration/server-config/named-collections).

    **Example**

    ```sql theme={null}
    CREATE TABLE deltalake
    ENGINE = DeltaLake('http://mars-doc-test.s3.amazonaws.com/clickhouse-bucket-3/test_table/', 'ABC123', 'Abc+123')
    ```

    Using named collections:

    ```xml theme={null}
    <clickhouse>
        <named_collections>
            <deltalake_conf>
                <url>http://mars-doc-test.s3.amazonaws.com/clickhouse-bucket-3/</url>
                <access_key_id>ABC123</access_key_id>
                <secret_access_key>Abc+123</secret_access_key>
            </deltalake_conf>
        </named_collections>
    </clickhouse>
    ```

    ```sql theme={null}
    CREATE TABLE deltalake
    ENGINE = DeltaLake(deltalake_conf, filename = 'test_table')
    ```
  </Tab>

  <Tab title="GCP">
    **Syntax**

    ```sql theme={null}
    -- Using HTTPS URL (recommended)
    CREATE TABLE table_name
    ENGINE = DeltaLake('https://storage.googleapis.com/<bucket>/<path>/', '<access_key_id>', '<secret_access_key>')
    ```

    <Info>
      **Unsupported gsutil URI**

      gsutil URI such as `gs://clickhouse-docs-example-bucket` is not supported, please use a URL starting `https://storage.googleapis.com`
    </Info>

    **Arguments**

    * `url` — GCS bucket URL to the Delta Lake table. Must use `https://storage.googleapis.com/<bucket>/<path>/`
      format (the GCS XML API endpoint), or `gs://<bucket>/<path>/` which is auto-converted.
    * `access_key_id` — GCS Access Key. Create via Google Cloud Console → Cloud Storage → Settings → Interoperability.
    * `secret_access_key` — GCS secret.

    **Named collections**

    You can also use named collections.
    For example:

    ```sql theme={null}
    CREATE NAMED COLLECTION gcs_creds AS
    access_key_id = '<access_key>',
    secret_access_key = '<secret>';

    CREATE TABLE gcpDeltaLake
    ENGINE = DeltaLake(gcs_creds, url = 'https://storage.googleapis.com/<bucket>/<path>')
    ```
  </Tab>

  <Tab title="Azure">
    **Syntax**

    ```sql theme={null}
    CREATE TABLE table_name
    ENGINE = DeltaLake(connection_string|storage_account_url, container_name, blobpath, [account_name, account_key, format, compression])
    ```

    **Arguments**

    * `connection_string` — Azure connection string
    * `storage_account_url` — Azure storage account URL (e.g., [https://account.blob.core.windows.net](https://account.blob.core.windows.net))
    * `container_name` — Azure container name
    * `blobpath` — Path to the Delta Lake table within the container
    * `account_name` — Azure storage account name
    * `account_key` — Azure storage account key
  </Tab>
</Tabs>

<h2 id="insert-data">
  Write data using a DeltaLake table
</h2>

Once you have created a table using the DeltaLake table engine, you can insert data into it with:

```sql theme={null}
SET allow_experimental_delta_lake_writes = 1;

INSERT INTO deltalake(id, firstname, lastname, gender, age)
VALUES (1, 'John', 'Smith', 'M', 32);
```

<Note>
  Writing using the table engine is supported only through delta kernel.
  Writes to Azure are not yet supported but work for S3 and GCS.
</Note>

<h3 id="data-cache">
  Data cache
</h3>

The `DeltaLake` table engine and table function support data caching, the same as `S3`, `AzureBlobStorage`, `HDFS` storages. See ["S3 table engine"](/reference/engines/table-engines/integrations/s3#data-cache) for more details.

<h2 id="see-also">
  See also
</h2>

* [deltaLake table function](/reference/functions/table-functions/deltalake)