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

# BigTable Connector | OpenMetadata Database Integration

> Connect Google Cloud Bigtable to OpenMetadata with our comprehensive database connector guide. Setup instructions, configuration steps, and metadata extraction tips.

export const MetadataIngestionUi = ({connector, selectServicePath, addNewServicePath, serviceConnectionPath}) => {
  return <>
    <p>
      To ingest metadata from your sources, you need to create a service connection.
      The service connects your source system with OpenMetadata. Once you create
      a service, you can use it to configure your ingestion workflows.<br />
      <br />
      To create a service connection and ingest your metadata, follow the steps below:
    </p>
      <Steps>
      <Step title="Select the Service">
        <ol>
          <li>
            On the left navigation bar, click <strong>Settings</strong>.
          </li>
          <li>
            On the next page, click <strong>Services</strong>, and then select the service.
            <img src="/public/images/connectors/visit-services-page.png" alt="Visit Services Page" />
          </li>
        </ol>
      </Step>

      <Step title="Create a New Service">
        To add a new service connection, click <strong>Add New Service</strong>.
        <img src="/public/images/connectors/create-new-service.png" alt="Create a new Service" />
      </Step>

      <Step title="Select the Connector">
        Select <strong>{connector}</strong> as the service type and click <strong>Next</strong>.

        {selectServicePath && <img src={selectServicePath} alt="Select Service" />}
      </Step>

      <Step title="Name and Describe the Service">
        Enter a unique <strong>Service Name</strong> and <strong>Description</strong>.
        <ul>
         <li><strong>Service Name</strong>: OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other services, including other {connector} services you are ingesting metadata from.</li>
        </ul>

        <Note>
          The service name cannot be changed after it is set.
       </Note>

        {addNewServicePath && <img src={addNewServicePath} alt="Add New Service" />}
      </Step>

      <Step title="Configure the Service Connection">
        Set up the connection settings required for {connector} to set up the service and start ingesting metadata from your sources. The right-hand panel displays help documentation for the selected connection type in the product UI.
        {serviceConnectionPath && <img src={serviceConnectionPath} alt="Configure Service connection" />}
      </Step>
    </Steps>
  </>;
};

export const ConnectorDetailsHeader = ({name, icon, stage, availableFeatures, unavailableFeatures = [], availableFeaturesCollate = []}) => {
  const showSubHeading = availableFeatures?.length > 0 || unavailableFeatures?.length > 0 || availableFeaturesCollate?.length > 0;
  const totalAvailableFeatures = [...availableFeatures || [], ...availableFeaturesCollate || []];
  return <div className="container">
      <div className="Heading">
        <div className="flex items-center gap-3">
          {icon && <div className="IconContainer">
              <img src={icon} alt={name} noZoom className="ConnectorIcon" />
            </div>}
          <h1 className="ConnectorName">{name}</h1>
          <span className={`StageBadge ${stage === 'PROD' ? 'prod' : 'beta'}`}>
            {stage}
          </span>
        </div>
      </div>
      {showSubHeading && <div className="SubHeading">
          <div className="FeaturesHeading">Feature List</div>
          <div className="FeaturesList">
            {totalAvailableFeatures.map(feature => <div className="FeatureTag AvailableFeature" key={feature}>
                ✓ {feature}
              </div>)}
            {unavailableFeatures.map(feature => <div className="FeatureTag UnavailableFeature" key={feature}>
                ✕ {feature}
              </div>)}
          </div>
        </div>}
    </div>;
};

<ConnectorDetailsHeader icon="/public/images/connectors/big-table.webp" name="BigTable" stage="PROD" availableFeatures={["Metadata"]} unavailableFeatures={["Query Usage", "Lineage", "Column-level Lineage", "Data Profiler", "Data Quality", "Owners", "dbt", "Tags", "Stored Procedures", "Sample Data", "Auto-Classification"]} />

In this section, we provide guides and references to use the BigTable connector.
Configure and schedule BigTable metadata and profiler workflows from the OpenMetadata UI:

* [Requirements](#requirements)
* [Metadata Ingestion](#metadata-ingestion)
* [Troubleshooting](/v1.12.x/connectors/database/bigtable/troubleshooting)

## How to Run the Connector Externally

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.

If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check
the following docs to run the Ingestion Framework **anywhere**.

<Columns cols={2}>
  <Card title="External Schedulers" href="/v1.12.x/deployment/ingestion">
    Get more information about running the Ingestion Framework Externally
  </Card>
</Columns>

## Requirements

### BigTable Admin API Permissions

* Go to [Cloud Bigtable Admin API in the GCP API Library](https://console.cloud.google.com/apis/library/bigtableadmin.googleapis.com)
* Select the `GCP Project ID`.
* Click on `Enable API` which will enable the data catalog api on the respective project.

### BigTable API Permissions

* Go to [Cloud Bigtable API in the GCP API Library](https://console.cloud.google.com/apis/library/bigtable.googleapis.com)
* Select the `GCP Project ID`.
* Click on `Enable API` which will enable the data catalog api on the respective project.

### GCP Permissions

To execute metadata extraction workflow successfully the user or the service account should have enough access to fetch required data. Following table describes the minimum required permissions

| #  | GCP Permission           | Required For       |
| :- | :----------------------- | :----------------- |
| 1  | bigtable.instances.get   | Metadata Ingestion |
| 2  | bigtable.instances.list  | Metadata Ingestion |
| 3  | bigtable.tables.get      | Metadata Ingestion |
| 4  | bigtable.tables.list     | Metadata Ingestion |
| 5  | bigtable.tables.readRows | Metadata Ingestion |

<Columns cols={2}>
  <Card title="Create Custom GCP Role" href="/v1.12.x/connectors/database/bigtable/roles">
    Checkout this documentation on how to create a custom role and assign it to the service account.
  </Card>
</Columns>

## Metadata Ingestion

<MetadataIngestionUi connector={"BigTable"} selectServicePath={"/public/images/connectors/bigtable/select-service.png"} addNewServicePath={"/public/images/connectors/bigtable/add-new-service.png"} serviceConnectionPath={"/public/images/connectors/bigtable/service-connection.png"} />

# Connection Options

<Steps>
  <Step title="Connection Options">
    **GCP Credentials**:
    You can authenticate with your BigTable instance using either `GCP Credentials Path` where you can specify the file path of the service account key or you can pass the values directly by choosing the `GCP Credentials Values` from the service account key file.
    You can checkout [this](https://cloud.google.com/iam/docs/keys-create-delete#iam-service-account-keys-create-console) documentation on how to create the service account keys and download it.
    **GCP Credentials Values**: Passing the raw credential values provided by BigTable. This requires us to provide the following information, all provided by BigTable:

    * **Credentials type**: Credentials Type is the type of the account, for a service account the value of this field is `service_account`. To fetch this key, look for the value associated with the `type` key in the service account key file.
    * **Project ID**: A project ID is a unique string used to differentiate your project from all others in Google Cloud. To fetch this key, look for the value associated with the `project_id` key in the service account key file. You can also pass multiple project id to ingest metadata from different BigTable projects into one service.
    * **Private Key ID**: This is a unique identifier for the private key associated with the service account. To fetch this key, look for the value associated with the `private_key_id` key in the service account file.
    * **Private Key**: This is the private key associated with the service account that is used to authenticate and authorize access to BigTable. To fetch this key, look for the value associated with the `private_key` key in the service account file.
    * **Client Email**: This is the email address associated with the service account. To fetch this key, look for the value associated with the `client_email` key in the service account key file.
    * **Client ID**: This is a unique identifier for the service account. To fetch this key, look for the value associated with the `client_id` key in the service account key  file.
    * **Auth URI**: This is the URI for the authorization server. To fetch this key, look for the value associated with the `auth_uri` key in the service account key file. The default value to Auth URI is [https://accounts.google.com/o/oauth2/auth](https://accounts.google.com/o/oauth2/auth).
    * **Token URI**: The Google Cloud Token URI is a specific endpoint used to obtain an OAuth 2.0 access token from the Google Cloud IAM service. This token allows you to authenticate and access various Google Cloud resources and APIs that require authorization. To fetch this key, look for the value associated with the `token_uri` key in the service account credentials file. Default Value to Token URI is [https://oauth2.googleapis.com/token](https://oauth2.googleapis.com/token).
    * **Authentication Provider X509 Certificate URL**: This is the URL of the certificate that verifies the authenticity of the authorization server. To fetch this key, look for the value associated with the `auth_provider_x509_cert_url` key in the service account key file. The Default value for Auth Provider X509Cert URL is [https://www.googleapis.com/oauth2/v1/certs](https://www.googleapis.com/oauth2/v1/certs)
    * **Client X509Cert URL**: This is the URL of the certificate that verifies the authenticity of the service account. To fetch this key, look for the value associated with the `client_x509_cert_url` key in the service account key  file.
      **GCP Credentials Path**: Passing a local file path that contains the credentials.

    <Tip>
      If you want to use [ADC authentication](https://cloud.google.com/docs/authentication#adc) for BigTable you can just leave
      the GCP credentials empty. This is why they are not marked as required.
    </Tip>
  </Step>

  <Step title="Advanced Configuration">
    Database Services have an Advanced Configuration section, where you can pass extra arguments to the connector
    and, if needed, change the connection Scheme.

    This would only be required to handle advanced connectivity scenarios or customizations.

    * **Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to database during the connection. These details must be added as Key-Value pairs.
    * **Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent during the connection. These details must be added as Key-Value pairs.

          <img src="https://mintcdn.com/openmetadata/6gXrLELUGeLr2Cj6/public/images/connectors/advanced-configuration.png?fit=max&auto=format&n=6gXrLELUGeLr2Cj6&q=85&s=c8f582832bafdb22aec9a99e387d8b50" alt="Advanced Configuration" width="1398" height="534" data-path="public/images/connectors/advanced-configuration.png" />
  </Step>

  <Step title="Test the Connection">
    Once the credentials have been added, click on *Test Connection* and *Save* the changes.

    <img src="https://mintcdn.com/openmetadata/9G75p72jJKYgvFUQ/public/images/connectors/test-connection.png?fit=max&auto=format&n=9G75p72jJKYgvFUQ&q=85&s=4ac71a56e30fa3dd1be86f82c1f07068" alt="Test Connection" width="1494" height="310" data-path="public/images/connectors/test-connection.png" />
  </Step>

  <Step title="Configure Metadata Ingestion">
    In this step we will configure the metadata ingestion pipeline,
    Please follow the instructions below

    <img src="https://mintcdn.com/openmetadata/9SXjaLbGROaofLQU/public/images/connectors/configure-metadata-ingestion-database-1.png?fit=max&auto=format&n=9SXjaLbGROaofLQU&q=85&s=88d2b5053db43d64f42deb9c7f1482c9" alt="Configure Metadata Ingestion" width="1327" height="1271" data-path="public/images/connectors/configure-metadata-ingestion-database-1.png" />

    <img src="https://mintcdn.com/openmetadata/9SXjaLbGROaofLQU/public/images/connectors/configure-metadata-ingestion-database-2.png?fit=max&auto=format&n=9SXjaLbGROaofLQU&q=85&s=e71e7a62c5d9be44458c87508fed39e1" alt="Configure Metadata Ingestion" width="1327" height="1271" data-path="public/images/connectors/configure-metadata-ingestion-database-2.png" />

    #### Metadata Ingestion Options

    <Tip>
      If the owner's name is openmetadata, you need to enter `openmetadata@domain.com` in the name section of add team/user form, click [here](/connectors/database/dbt/ingest-dbt-owner#following-steps-shows-adding-a-user-to-openmetadata) for more info.
    </Tip>

    * **Name**: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.

    * **Database Filter Pattern (Optional)**: Use to database filter patterns to control whether or not to include database as part of metadata ingestion.
      * **Include**: Explicitly include databases by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all databases with names matching one or more of the supplied regular expressions. All other databases will be excluded.
      * **Exclude**: Explicitly exclude databases by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all databases with names matching one or more of the supplied regular expressions. All other databases will be included.

    * **Schema Filter Pattern (Optional)**: Use to schema filter patterns to control whether to include schemas as part of metadata ingestion.
      * **Include**: Explicitly include schemas by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all schemas with names matching one or more of the supplied regular expressions. All other schemas will be excluded.
      * **Exclude**: Explicitly exclude schemas by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all schemas with names matching one or more of the supplied regular expressions. All other schemas will be included.

    * **Table Filter Pattern (Optional)**: Use to table filter patterns to control whether to include tables as part of metadata ingestion.
      * **Include**: Explicitly include tables by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all tables with names matching one or more of the supplied regular expressions. All other tables will be excluded.
      * **Exclude**: Explicitly exclude tables by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all tables with names matching one or more of the supplied regular expressions. All other tables will be included.

    * **Enable Debug Log (toggle)**: Set the Enable Debug Log toggle to set the default log level to debug.

    * **Mark Deleted Tables (toggle)**: Set the Mark Deleted Tables toggle to flag tables as soft-deleted if they are not present anymore in the source system.

    * **Mark Deleted Tables from Filter Only (toggle)**: Set the Mark Deleted Tables from Filter Only toggle to flag tables as soft-deleted if they are not present anymore within the filtered schema or database only. This flag is useful when you have more than one ingestion pipelines. For example if you have a schema

    * **includeTables (toggle)**: Optional configuration to turn off fetching metadata for tables.

    * **includeViews (toggle)**: Set the Include views toggle to control whether to include views as part of metadata ingestion.

    * **includeTags (toggle)**: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.

    * **includeOwners (toggle)**: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.

    * **includeStoredProcedures (toggle)**: Optional configuration to toggle the Stored Procedures ingestion.

    * **includeDDL (toggle)**: Optional configuration to toggle the DDL Statements ingestion.

    * **queryLogDuration (Optional)**: Configuration to tune how far we want to look back in query logs to process Stored Procedures results.

    * **queryParsingTimeoutLimit (Optional)**: Configuration to set the timeout for parsing the query in seconds.

    * **useFqnForFiltering (toggle)**: Regex will be applied on fully qualified name (e.g service\_name.db\_name.schema\_name.table\_name) instead of raw name (e.g. table\_name).

    * **Incremental (Beta)**: Use Incremental Metadata Extraction after the first execution. This is done by getting the changed tables instead of all of them. **Only Available for BigQuery, Redshift and Snowflake**
      * **Enabled**: If `True`, enables Metadata Extraction to be Incremental.
      * **lookback Days**: Number of days to search back for a successful pipeline run. The timestamp of the last found successful pipeline run will be used as a base to search for updated entities.
      * **Safety Margin Days**: Number of days to add to the last successful pipeline run timestamp to search for updated entities.

    * **Threads (Beta)**: Use a Multithread approach for Metadata Extraction. You can define here the number of threads you would like to run concurrently.

    Note that the right-hand side panel in the OpenMetadata UI will also share useful documentation when configuring the ingestion.
  </Step>

  <Step title="Schedule the Ingestion and Deploy">
    Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The
    timezone is in UTC. Select a Start Date to schedule for ingestion. It is
    optional to add an End Date.

    Review your configuration settings. If they match what you intended,
    click Deploy to create the service and schedule metadata ingestion.

    If something doesn't look right, click the Back button to return to the
    appropriate step and change the settings as needed.

    After configuring the workflow, you can click on Deploy to create the
    pipeline.

    <img src="https://mintcdn.com/openmetadata/j50Bw6ZBiFbbFFnF/public/images/connectors/schedule.png?fit=max&auto=format&n=j50Bw6ZBiFbbFFnF&q=85&s=24b0c2f55f803efde5fb3b3bc24ed3ae" alt="Schedule the Workflow" width="2733" height="1083" data-path="public/images/connectors/schedule.png" />
  </Step>

  <Step title="View the Ingestion Pipeline">
    Once the workflow has been successfully deployed, you can view the
    Ingestion Pipeline running from the Service Page.

    <img src="https://mintcdn.com/openmetadata/9G75p72jJKYgvFUQ/public/images/connectors/view-ingestion-pipeline.png?fit=max&auto=format&n=9G75p72jJKYgvFUQ&q=85&s=7c4e411977371617cb1312efb9f9bfee" alt="View Ingestion Pipeline" width="2733" height="1271" data-path="public/images/connectors/view-ingestion-pipeline.png" />

    <Tip>
      If AutoPilot is enabled, workflows like usage tracking, data lineage, and similar tasks will be handled automatically. Users don’t need to set up or manage them - AutoPilot takes care of everything in the system.
    </Tip>
  </Step>
</Steps>