Druid connector#

The Druid connector allows querying an Apache Druid database from Trino.


To connect to Druid, you need:

  • Druid version 0.18.0 or higher.

  • Network access from the Trino coordinator and workers to your Druid broker. Port 8082 is the default port.


Create a catalog properties file that specifies the Druid connector by setting the connector.name to druid and configuring the connection-url with the JDBC string to connect to Druid.

For example, to access a database as druid, create the file etc/catalog/druid.properties. Replace BROKER:8082 with the correct host and port of your Druid broker.


You can add authentication details to connect to a Druid deployment that is secured by basic authentication by updating the URL and adding credentials:


Now you can access your Druid database in Trino with the druiddb catalog name from the properties file.

General configuration properties#

The following table describes general catalog configuration properties for the connector:

Property name


Default value


Support case insensitive schema and table names.





Path to a name mapping configuration file in JSON format that allows Trino to disambiguate between schemas and tables with similar names in different cases.



Frequency with which Trino checks the name matching configuration file for changes.

0 (refresh disabled)


Duration for which metadata, including table and column statistics, is cached.

0 (caching disabled)


Cache the fact that metadata, including table and column statistics, is not available



Maximum number of objects stored in the metadata cache



Maximum number of statements in a batched execution. Do not change this setting from the default. Non-default values may negatively impact performance.



Push down dynamic filters into JDBC queries



Maximum duration for which Trino will wait for dynamic filters to be collected from the build side of joins before starting a JDBC query. Using a large timeout can potentially result in more detailed dynamic filters. However, it can also increase latency for some queries.


Domain compaction threshold#

Pushing down a large list of predicates to the data source can compromise performance. Trino compacts large predicates into a simpler range predicate by default to ensure a balance between performance and predicate pushdown. If necessary, the threshold for this compaction can be increased to improve performance when the data source is capable of taking advantage of large predicates. Increasing this threshold may improve pushdown of large dynamic filters. The domain-compaction-threshold catalog configuration property or the domain_compaction_threshold catalog session property can be used to adjust the default value of 32 for this threshold.


  • system.flush_metadata_cache()

    Flush JDBC metadata caches. For example, the following system call flushes the metadata caches for all schemas in the example catalog

    USE example.myschema;
    CALL system.flush_metadata_cache();

Case insensitive matching#

When case-insensitive-name-matching is set to true, Trino is able to query non-lowercase schemas and tables by maintaining a mapping of the lowercase name to the actual name in the remote system. However, if two schemas and/or tables have names that differ only in case (such as “customers” and “Customers”) then Trino fails to query them due to ambiguity.

In these cases, use the case-insensitive-name-matching.config-file catalog configuration property to specify a configuration file that maps these remote schemas/tables to their respective Trino schemas/tables:

  "schemas": [
      "remoteSchema": "CaseSensitiveName",
      "mapping": "case_insensitive_1"
      "remoteSchema": "cASEsENSITIVEnAME",
      "mapping": "case_insensitive_2"
  "tables": [
      "remoteSchema": "CaseSensitiveName",
      "remoteTable": "tablex",
      "mapping": "table_1"
      "remoteSchema": "CaseSensitiveName",
      "remoteTable": "TABLEX",
      "mapping": "table_2"

Queries against one of the tables or schemes defined in the mapping attributes are run against the corresponding remote entity. For example, a query against tables in the case_insensitive_1 schema is forwarded to the CaseSensitiveName schema and a query against case_insensitive_2 is forwarded to the cASEsENSITIVEnAME schema.

At the table mapping level, a query on case_insensitive_1.table_1 as configured above is forwarded to CaseSensitiveName.tablex, and a query on case_insensitive_1.table_2 is forwarded to CaseSensitiveName.TABLEX.

By default, when a change is made to the mapping configuration file, Trino must be restarted to load the changes. Optionally, you can set the case-insensitive-name-mapping.refresh-period to have Trino refresh the properties without requiring a restart:


Type mapping#

Because Trino and Druid each support types that the other does not, this connector modifies some types when reading data.

Druid type to Trino type mapping#

The connector maps Druid types to the corresponding Trino types according to the following table:

Druid type to Trino type mapping#

Druid type

Trino type










Except for the special _time column, which is mapped to TIMESTAMP.



Only applicable to the special _time column.

No other data types are supported.

Druid does not have a real NULL value for any data type. By default, Druid treats NULL as the default value for a data type. For example, LONG would be 0, DOUBLE would be 0.0, STRING would be an empty string '', and so forth.

Type mapping configuration properties#

The following properties can be used to configure how data types from the connected data source are mapped to Trino data types and how the metadata is cached in Trino.

Property name


Default value


Configure how unsupported column data types are handled:

  • IGNORE, column is not accessible.

  • CONVERT_TO_VARCHAR, column is converted to unbounded VARCHAR.

The respective catalog session property is unsupported_type_handling.



Allow forced mapping of comma separated lists of data types to convert to unbounded VARCHAR

SQL support#

The connector provides globally available and read operation statements to access data and metadata in the Druid database.

Table functions#

The connector provides specific table functions to access Druid.

query(varchar) -> table#

The query function allows you to query the underlying database directly. It requires syntax native to Druid, because the full query is pushed down and processed in Druid. This can be useful for accessing native features which are not available in Trino or for improving query performance in situations where running a query natively may be faster.


Polymorphic table functions may not preserve the order of the query result. If the table function contains a query with an ORDER BY clause, the function result may not be ordered as expected.

As an example, use STRING_TO_MV and MV_LENGTH from Druid SQL’s multi-value string functions to split and then count the number of comma-separated values in a column:

      query => 'SELECT
          STRING_TO_MV(direct_reports, ",")
        ) AS num_reports
      FROM company.managers'