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You are viewing documentation for Immuta version 2020.2.

For the latest version, view our documentation for Immuta SaaS or the latest self-hosted version.

Query-backed and Object-backed Data Sources

Audience: Data Owners

Content Summary: This section includes guides for creating query-backed data sources and object-backed data sources in Immuta.

For a discussion of the concepts and philosophies behind Immuta data sources, navigate to the data source entry in the Immuta Glossary.

Query-backed Data Sources

Query-backed data sources are accessible to subscribed data consumers via our Immuta Query Engine and appear as though they are Postgres tables.

The storage technologies relevant to this tutorial are listed below. Hyperlinked technologies require special consideration.

  • Amazon Athena
  • Amazon Redshift
  • Azure SQL Data Warehouse
  • BigQuery
  • Databricks
  • ElasticSearch
  • Greenplum
  • HIVE
  • IBM Netezza
  • Impala
  • MariaDB
  • MemSQL
  • MS SQL Server
  • MySQL
  • Oracle
  • PostgreSQL
  • Presto
  • Snowflake
  • Teradata
  • Vertica

Schema Namespace Support

As a Data Owner, you can specify the schema in which to create the SQL-queryable table reference; this allows you to mirror the source schema name, incorporate the source database and source schema in the schema name, or organize data sources any way that you want.

If you do not specify the schema or the schema does not exist, the schema will be automatically created. If a data source is deleted and there are no other tables in the schema, the schema will automatically be dropped (except for the schemas immuta and public).

Object-backed Data Sources

Object-backed data sources are data storage technologies that do not support SQL and can range from NoSQL technologies, to blob stores, to filesystems, to APIs.

The storage technologies relevant to this tutorial are listed below. Hyperlinks provide specific instructions for each technology.