They provide SQL integration with any database via several connectors (native, JDBC, SQL Alchemy…).
Other modes like MapReduce, Java, Shell, Sqoop are also available. Here is a list of the existing connectors.
The Editor Configuration also describes the configuration steps.
Close to 100% of Hive and Impala grammar is supported which makes the autocomplete extremly powerful. Other languages defaults to a generic SQL grammar.
Coming Soon How to write your own SQL parser.
Hive, Impala, SparkSQL
SQL Alchemy is the prefered way if the HiveServer2 API is not supported by the database. More enterprise support will come with HUE-8740.
MySQL, Oracle, PostgreSQL, Phoenix, Presto, Kylin, Redshift, BigQuery, Drill
Use the query editor with any JDBC compatible database. View the JDBC connector.
Note Going forward, SQL Alchemy is prefered as more “Python native”.
The Job Browser is generic and can list any type of jobs, queries and provide bulk operations like kill, pause, delete… and access to logs and recommendations.
MapReduce, Pig, Java, Shell, Sqoop, DistCp Oozie connector
Based on the Livy REST API
Dashboards are generic and support Solr and any SQL:
The API was influenced by Solr but is now generic:
When HS2, RDBMS, and JDBC Are Not Enough
If the built-in HiveServer2 (Hive, Impala, Spark SQL), RDBMS (MySQL, PostgreSQL, Oracle, SQLite), and JDBC interfaces don’t meet your needs, you can implement your own connector to the notebook app: Notebook Connectors. Each connector API subclasses the Base API and must implement the methods defined within; refer to the JdbcApi or RdbmsApi for representative examples.
A connector similar to Solr or SQL Alchemy binding would need to be developed HUE-7828