Looker supports a wide range of SQL database dialects and continues to improve the feature implementations for existing dialect options as well as add new dialects. Because our modeling layer, LookML, builds on top of the in-database features available, some dialects allow for a more powerful implementation than others.
Support levels and JDBC installation
Looker has two support levels for dialects based on a dialect's built-in feature set and the level of demand by Looker users:
Supported: A dialect that is fully supported by Looker. Looker is committed to improving this dialect implementation and will fix issues based on severity and demand. Looker runs exhaustive tests against this dialect at least weekly to ensure quality.
Integration: A dialect that is partially supported. Looker is able to connect to this dialect, but there are no commitments to improve implementation, fix issues, or regularly run tests against the dialect.
For the dialects whose value of JDBC Driver Included? is No, the needed JDBC JAR file is not bundled with the Looker JAR files. For customer-hosted installations of Looker, you must configure the driver for use with Looker as described on the Unpackaged JDBC drivers documentation page.
Looker (original) supports the following SQL dialects as of Looker 26.0:
| Dialect | Support Level | JDBC Driver Included? |
|---|---|---|
| Actian Avalanche | Supported | |
| Amazon Athena | Supported | |
| Amazon Aurora MySQL | Supported | |
| Amazon Redshift | Supported | |
| Amazon Redshift 2.1+ | Supported | |
| Amazon Redshift Serverless 2.1+ | Supported | |
| Apache Druid | Supported | |
| Apache Druid 0.13+ | Supported | |
| Apache Druid 0.18+ | Supported | |
| Apache Hive 2.3+ | Integration | |
| Apache Hive 3.1.2+ | Supported | |
| Apache Spark 3+ | Supported | |
| ClickHouse | Supported | |
| Cloudera Impala 3.1+ | Supported | |
| Cloudera Impala 3.1+ with Native Driver | Supported | |
| Cloudera Impala with Native Driver | Supported | |
| DataVirtuality | Supported | |
| Databricks | Supported | |
| Denodo 7 | Supported | |
| Denodo 8 & 9 | Supported | |
| Dremio | Supported | |
| Dremio 11+ | Supported | |
| Exasol | Supported | |
| Google BigQuery Legacy SQL | Supported | |
| Google BigQuery Standard SQL | Supported | |
| Google Cloud PostgreSQL | Supported | |
| Google Cloud SQL | Supported | |
| Google Spanner | Supported | |
| Greenplum | Supported | |
| HyperSQL | Integration | |
| IBM Netezza | Integration | |
| MariaDB | Supported | |
| Microsoft Azure PostgreSQL | Supported | |
| Microsoft Azure SQL Database | Supported | |
| Microsoft Azure Synapse Analytics | Supported | |
| Microsoft SQL Server 2008+ | Integration | |
| Microsoft SQL Server 2012+ | Integration | |
| Microsoft SQL Server 2016 | Supported | |
| Microsoft SQL Server 2017+ | Supported | |
| MongoBI | Supported | |
| MySQL | Supported | |
| MySQL 8.0.12+ | Supported | |
| Oracle | Supported | |
| Oracle ADWC | Integration | |
| PostgreSQL 9.5+ | Supported | |
| PostgreSQL pre-9.5 | Integration | |
| PrestoDB | Supported | |
| PrestoSQL | Supported | |
| SAP HANA | Supported | |
| SAP HANA 2+ | Supported | |
| SingleStore | Supported | |
| SingleStore 7+ | Supported | |
| Snowflake | Supported | |
| Teradata | Supported | |
| Trino | Supported | |
| Vector | Supported | |
| Vertica | Supported |
Database configuration instructions
Instructions are available for these SQL dialects:
Looker does not support new connections for the following dialects. Existing connections will continue to function as expected. For Looker instances with existing connections to these dialects, the following links to documentation are provided for reference:
Looker also connects with the following dialects. Reach out to your Looker contact for assistance.
- IBM Netezza
Next steps
After you configure your database to work with Looker, you're ready to connect Looker to your database.