Data Platforms Overview

Immuta does not require users to learn a new API or language to access protected data. Instead, Immuta integrates with existing tools and data platforms while remaining invisible to downstream consumers.

The table below outlines features supported by each of Immuta's data platform integrations.

	Marketplace	Subscription policies	Data policies	Identification	Query audit	Tag ingestion
Amazon Redshift view-based integration	✅	✅	✅	✅	❌	❌
Amazon Redshift viewless integration	✅	❌	❌	❌	❌	❌
Amazon S3	✅	✅	❌	✅	❌	❌
AWS Lake Formation	✅	✅	❌	✅	❌	❌
Azure Synapse Analytics	✅	✅	✅	✅	❌	❌
Databricks Spark	✅	✅	✅	✅	✅	❌
Databricks Unity Catalog	✅	✅	✅	✅	✅	✅
Google BigQuery	✅	✅	✅	✅	❌	❌
MariaDB	✅	❌	❌	❌	❌	❌
Oracle	✅	❌	❌	✅	N/A	❌
PostgreSQL	✅	✅	❌	✅	❌	❌
Snowflake	✅	✅	✅	✅	✅	✅
SQL Server	✅	❌	❌	✅	❌	❌
Starburst (Trino)	✅	✅	✅	✅	✅	❌
Teradata	✅	✅	❌	✅	❌	❌

Subscription policy support matrix

The table below illustrates the subscription policy access types supported by each integration. If a data platform isn't included in the table, that integration does not support any subscription policies. For more details about read and write access policy support for these data platforms, see the Subscription policy access types reference guide.

Data platform	Read access policies	Write access policies
Amazon Redshift view-based integration	✅	❌ View-based integrations are read-only
Amazon S3	✅	✅
AWS Lake Formation	✅	✅
Azure Synapse Analytics	✅	❌ View-based integrations are read-only
Databricks Spark	✅	❌ Write access is controlled through workspaces and scratch paths
Databricks Unity Catalog	✅	✅
Google BigQuery	✅	❌ View-based integrations are read-only
PostgreSQL	✅	✅
Snowflake	✅	✅
Starburst (Trino)	✅	✅
Teradaata	✅	❌

Data policy support matrix

The table below outlines the types of data policies supported for various data platforms. If a data platform isn't included in the table, that integration does not support any data policies.

For details about each of these policies, see the Data policy types page.

	Amazon Redshift view-based integration	Azure Synapse Analytics	Databricks Spark	Databricks Unity Catalog	Google BigQuery	Snowflake	Starburst (Trino)
Reversible masking	✅	❌	✅	❌	❌	✅	✅
Conditional masking	✅	✅	✅	✅	❌	✅	✅
Hashing	✅	✅	✅	✅	✅	✅	✅
Replace with NULL or constant	✅	✅		✅	✅	✅	✅
Rounding	✅	✅	✅	✅	✅	✅	✅
Regex	✅	❌	✅	✅	✅	✅	✅
Format preserving masking	❌	❌	❌	❌	❌	✅	❌
Randomized response	❌	❌	❌	❌	❌	✅	❌
Masking fields within STRUCT columns	❌	❌	✅		❌	❌	❌
	✅	✅	✅	✅	✅	✅	✅
Only show data by time	✅	✅	✅	✅	✅	✅	✅
Minimize	✅	✅	✅	✅	✅	✅	✅
WHERE clause	✅	✅	✅	✅	✅	✅	✅
Matching	✅	✅	✅	✅	✅	✅	✅

Identification support matrix

Identification has varied support for data sources from different technologies based on the identifier type. For details about how identification works in Immuta, see the Data identification page.

Technology	Regex	Dictionary	Column name regex
Amazon Redshift view-based integration	✅	✅	✅
Amazon Redshift viewless integration	❌	❌	❌
Amazon S3	❌	❌	✅
AWS Lake Formation	❌	❌	✅
Azure Synapse Analytics	❌	❌	✅
Databricks	✅	✅	✅
Google BigQuery	❌	❌	✅
MariaDB	❌	❌	❌
Oracle	❌	❌	✅
PostgreSQL	❌	❌	✅
Snowflake	✅	✅	✅
SQL Server	❌	❌	✅
Starburst (Trino)	✅	✅	✅
Teradata	❌	❌	✅

Query audit support for platform queries

The table below outlines what information is included in the query audit logs for each integration where query audit is supported.

	Snowflake	Databricks Spark	Databricks Unity Catalog	Starburst (Trino)
Table and user coverage	Registered data sources and users	Registered data sources and users	All tables and users	Registered data sources and users
Object queried	✅	✅	✅	✅
Columns returned	✅	❌	✅	✅
Rows returned	✅	❌	✅	✅
Query text	✅	✅	✅	✅
Unauthorized information		✅	✅	❌

Legend:

• ✅ This is available and the information is included in audit logs.

• ❌ This is not available and the information is not included in audit logs.