Looker dialects

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 26.2:

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 AlloyDB for PostgreSQL	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 .