Skip to main content
In this section, we provide guides and references to use the S3 Datalake connector. Configure and schedule S3 Datalake metadata and profiler workflows from the OpenMetadata UI:

Requirements

Before configuring the S3 Datalake connector, make sure the following requirements are in place.
The S3 Datalake connector supports extracting metadata from file types JSON, CSV, TSV & Parquet.

S3 Permissions

To execute metadata extraction AWS account should have enough access to fetch required data. The Bucket Policy in AWS requires at least these permissions:

Metadata Ingestion

To ingest metadata from S3 Datalake, you need to create a service connection. The service connects S3 Datalake with OpenMetadata. Once you create a service, OpenMetadata automatically starts ingesting metadata.

Step 1: Add New Service

  1. Navigate to Settings > Services. Navigate to Settings and Services
  2. Click Add New Service. Add New Service

Step 2: Select a Service and Connector

From the service type dropdown, select Database Services, then click the S3 Datalake connector tile. Select Service

Step 3: Add Service Name and Description

  • Enter a unique, descriptive Service Name. OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other S3 Datalake services you are ingesting metadata from.
  • Optional: Enter a Description for the service.
Configure Service
Note: The service name cannot be changed after it is set.

Step 4: Configure Connection Options

Specify your source credentials and verify the connection.

Enter Connection Details

Enter the connection details for S3 Datalake. The right-hand panel in the UI displays inline help for each field. Configure Service Connection
  • AWS Access Key ID and AWS Secret Access Key: When you interact with AWS, you specify your AWS security credentials to verify who you are and whether you have permission to access the resources that you are requesting. AWS uses the security credentials to authenticate and authorize your requests (docs). Access keys consist of two parts: An access key ID (for example, AKIAIOSFODNN7EXAMPLE), and a secret access key (for example, wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY). You must use both the access key ID and secret access key together to authenticate your requests. You can find further information on how to manage your access keys.
  • AWS Region: Each AWS Region is a separate geographic area in which AWS clusters data centers (docs). As AWS can have instances in multiple regions, we need to know the region the service you want to reach belongs to. Note that the AWS Region is the only required parameter when configuring a connection. When connecting to the services programmatically, there are different ways in which we can extract and use the rest of AWS configurations. You can find further information about configuring your credentials.
  • AWS Session Token (optional): If you are using temporary credentials to access your services, you will need to inform the AWS Access Key ID and AWS Secrets Access Key. Also, these will include an AWS Session Token. You can find more information on Using temporary credentials with AWS resources.
  • Endpoint URL (optional): To connect programmatically to an AWS service, you use an endpoint. An endpoint is the URL of the entry point for an AWS web service. The AWS SDKs and the AWS Command Line Interface (AWS CLI) automatically use the default endpoint for each service in an AWS Region. But you can specify an alternate endpoint for your API requests. Find more information on AWS service endpoints.
  • Profile Name: A named profile is a collection of settings and credentials that you can apply to an AWS CLI command. When you specify a profile to run a command, the settings and credentials are used to run that command. Multiple named profiles can be stored in the config and credentials files. You can inform this field if you’d like to use a profile other than default. Find more information about Named profiles for the AWS CLI.
  • Assume Role Arn: Typically, you use AssumeRole within your account or for cross-account access. In this field you’ll set the ARN (Amazon Resource Name) of the policy of the other account. A user who wants to access a role in a different account must also have permissions that are delegated from the account administrator. The administrator must attach a policy that allows the user to call AssumeRole for the ARN of the role in the other account. This is a required field if you’d like to AssumeRole. Find more information on AssumeRole.
When using Assume Role authentication, ensure you provide the following details:
  • AWS Region: Specify the AWS region for your deployment.
  • Assume Role ARN: Provide the ARN of the role in your AWS account that OpenMetadata will assume.
  • Assume Role Session Name: An identifier for the assumed role session. Use the role session name to uniquely identify a session when the same role is assumed by different principals or for different reasons. By default, we’ll use the name OpenMetadataSession. Find more information about the Role Session Name.
  • Assume Role Source Identity: The source identity specified by the principal that is calling the AssumeRole operation. You can use source identity information in AWS CloudTrail logs to determine who took actions with a role. Find more information about Source Identity.

Test Connection

Once the credentials have been added, click on Test Connection and Save the changes. Test Connection

Step 5: Configure Ingestion Options

In the What to Ingest step, use filter patterns to control which assets OpenMetadata ingests from your database service. Filter patterns use regular expressions applied to asset names.

How Filter Patterns Work

  • Include: Add one or more comma-separated regular expressions. OpenMetadata ingests only assets whose names match at least one expression. Leave blank to include all assets.
  • Exclude: Add one or more comma-separated regular expressions. OpenMetadata skips any asset whose name matches an expression. Leave blank to exclude nothing.
Rules match asset names using one of five expressions:
  • contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
  • starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
  • ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
  • is exactly: matches the exact name only. For example, analytics matches only analytics.
  • matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.
When both Include and Exclude are set, Exclude takes priority.
Leave all filter patterns empty to ingest all databases, schemas, and tables available in the source.
Filter Options The Database, Schema, and Table sections each include the following filter options:
  • Database: Controls which databases OpenMetadata ingests from the source.
  • Schema: Controls which schemas within the ingested databases are included.
  • Table: Controls which tables and views within the ingested schemas are included.
Each section provides the following controls:
  • Scan Mode: You can choose between the following scan modes:
    • Scan all: Ingests every asset of that type the connector can access. This is the default.
    • Only specific: Enables include rules so only assets matching at least one rule are ingested.
  • Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector, for example, Exclude system databases for the Databases section.
  • Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
  • Preview: Shows a real-time summary of what will be in scope based on your current rules.
  • Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.

Step 6: Create & Deploy

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. OpenMetadata saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Settings > Services and select your service.

Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts schemas, tables, columns, and other structural metadata from your source and keeps your OpenMetadata catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, OpenMetadata automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:
  1. Navigate to Settings > Services and select the service type. Navigate to Settings and Services
  2. Click the service you have added.
  3. Select the Agents tab and click Add Agent > Metadata. Add Metadata Agent For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
  4. On the Configure Ingestion page, do the following and click Next.
    • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline. Name this Ingestion
    • Agent Setup: Configure core parameters for metadata extraction. The following fields are available: Agent Setup
    • Filter Patterns: Apply include or exclude rules to scope which databases, schemas, tables, and stored procedures this agent ingests. For more information about various filter options, see Step 6: Configure Ingestion Options. Filter Patterns
    • Scope & Behaviour: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:
      Available toggles vary by connector. Stored procedure options only appear for connectors that support stored procedures.
      Scope & Behaviour
    • Advanced Config: Optional connector-specific settings such as Include Views and Extract JSON Schema. Advanced Config
  5. On the Schedule Interval page, set when the agent runs:
    • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
    • On-Demand: No automatic schedule; trigger the agent manually when needed.
    Schedule Interval
  6. Click Add to deploy the agent.

Usage Workflow

Learn more about how to configure the Usage Workflow to ingest Query information from the UI.

Lineage Workflow

Learn more about how to configure the Lineage from the UI.

Profiler Workflow

Learn more about how to configure the Data Profiler from the UI.

Data Quality Workflow

Learn more about how to configure the Data Quality tests from the UI.

dbt Integration

Learn more about how to ingest dbt models’ definitions and their lineage.