Elastic PostgreSQL connector referenceedit

The Elastic PostgreSQL connector is a connector for PostgreSQL.

Availability and prerequisitesedit

This connector is available as a native connector in Elastic versions 8.8.0 and later. To use this connector as a native connector, satisfy all native connector requirements.

This connector is available as a connector client from the Python connectors framework. To use this connector, satisfy all connector client requirements.

This connector is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.


To use this connector as a native connector, use the Connector workflow. See Native connectors.

To use this connector as a connector client, see Connector clients and frameworks.

Users must set track_commit_timestamp to on. To do this, run ALTER SYSTEM SET track_commit_timestamp = on; in PostgreSQL server.

For additional operations, see Usage.

For an end-to-end example of the connector client workflow, see PostgreSQL connector client tutorial.


PostgreSQL versions 11 to 15 are compatible with Elastic connector frameworks.


When using the connector client workflow, initially these fields will use the default configuration set in the connector source code. Note that this data source uses the generic_database.py connector source code.

Refer to postgresql.py for additional code, specific to this data source. These configurable fields will be rendered with their respective labels in the Kibana UI. Once connected, users will be able to update these values in Kibana.

Set the following configuration fields:


The server host address where the PostgreSQL is hosted. Examples:

  • demo.instance.demo-region.demo.service.com

The port where the PostgreSQL is hosted. Examples:

  • 5432
  • 9090
The username of the PostgreSQL account.
The password of the PostgreSQL account.

Name of the PostgreSQL database. Examples:

  • employee_database
  • customer_database
Comma-separated List of Tables

A list of tables separated by commas. The PostgreSQL connector will fetch data from all tables present in the configured database, if the value is * . Default value is *. Examples:

  • table_1, table_2
  • *
Enable SSL
Whether SSL verification will be enabled. Default value is True.
SSL Certificate

Content of SSL certificate. If SSL is disabled, the ssl_ca value will be ignored.

Expand to see an example certificate

Deployment using Dockeredit

Follow these instructions to deploy the PostgreSQL connector using Docker.

Step 1: Download sample configuration file

Download the sample configuration file. You can either download it manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors-python/main/config.yml --output ~/connectors-python-config/config.yml

Remember to update the --output argument value if your directory name is different, or you want to use a different config file name.

Step 2: Update the configuration file for your self-managed connector

Update the configuration file with the following settings to match your environment:

  • elasticsearch.host
  • elasticsearch.password
  • connector_id
  • service_type

Use postgresql as the service_type value. Don’t forget to uncomment "postgresql" in the sources section of the yaml file.

If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:

  host: http://host.docker.internal:9200
  username: elastic
  password: <YOUR_PASSWORD>

service_type: postgresql

  # UNCOMMENT "postgresql" below to enable the PostgreSQL connector

  #mongodb: connectors.sources.mongo:MongoDataSource
  #s3: connectors.sources.s3:S3DataSource
  #dir: connectors.sources.directory:DirectoryDataSource
  #mysql: connectors.sources.mysql:MySqlDataSource
  #network_drive: connectors.sources.network_drive:NASDataSource
  #google_cloud_storage: connectors.sources.google_cloud_storage:GoogleCloudStorageDataSource
  #azure_blob_storage: connectors.sources.azure_blob_storage:AzureBlobStorageDataSource
  #postgresql: connectors.sources.postgresql:PostgreSQLDataSource
  #oracle: connectors.sources.oracle:OracleDataSource
  #mssql: connectors.sources.mssql:MSSQLDataSource

Note that the config file you downloaded might contain more entries, so you will need to manually copy/change the settings that apply to you. Normally you’ll only need to update elasticsearch.host, elasticsearch.password, connector_id and service_type to run the connector service.

Step 3: Run the Docker image

Run the Docker image with the Connector Service using the following command:

docker run \
-v ~/connectors-python-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors: \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to this guide in the Python framework repository for more details.

Documents and syncsedit

  • Tables must be owned by a PostgreSQL user.
  • Database superuser privileges are required to index all database tables.
  • Tables with no primary key defined are skipped.
  • To fetch the last updated time in PostgreSQL, track_commit_timestamp must be set to on. Otherwise, all data will be indexed in every sync.

Sync rulesedit

  • Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that deployment.
  • Filtering rules are not available in the present version. Currently filtering is controlled via ingest pipelines.

Content extractionedit

See Content extraction.

Connector client operationsedit

End-to-end testingedit

The connector framework enables operators to run functional tests against a real data source. Refer to Connector testing for more details.

To perform E2E testing for the PostgreSQL connector, run the following command:

$ make ftest NAME=postgresql

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=postgresql DATA_SIZE=small

Known issuesedit

There are no known issues for this connector. Refer to Known issues for a list of known issues for all connectors.


See Troubleshooting.


See Security.

Framework and sourceedit

This connector is included in the Python connectors framework.

This connector uses the generic database connector source code (branch 8.8, compatible with Elastic 8.8).

View additional code specific to this data source (branch 8.8, compatible with Elastic 8.8).