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Supported Enrichment Datastores

An enrichment datastore is a dedicated datastore linked to a source datastore that persists scan results, anomalies, remediation data, and source record examples. Not all connectors support enrichment — the tables below show which connectors can be used as enrichment datastores.

Enrichment support requires the connector to have write capabilities so that Qualytics can create and manage enrichment tables (source records, anomaly records, remediation tables, and metadata tables) in the target datastore.

Available Datastore Connectors

For the full list of all supported source datastore connectors (including those without enrichment support), see the Available Datastore Connectors page.

Enrichment Table Types

To understand the different table types created in an enrichment datastore (source records, anomaly records, remediation, metadata), see the Enrichment Table Types documentation.

JDBC Connectors

JDBC connectors that support enrichment can store scan results and anomaly data directly in the relational database. Out of 19 JDBC connectors, 11 support enrichment.

No. Connector Logo Enrichment Support
1. Athena Athena
2. BigQuery BigQuery
3. Databricks Databricks
4. DB2 DB2
5. Dremio Dremio
6. Fabric Analytics Fabric
7. Hive Hive
8. MariaDB MariaDB
9. Microsoft SQL Server SQL Server
10. MySQL MySQL
11. Oracle Oracle
12. PostgreSQL PostgreSQL
13. Presto Presto
14. Redshift Redshift
15. Snowflake Snowflake
16. Synapse Synapse
17. Teradata Teradata
18. TimescaleDB Timescale
19. Trino Trino

DFS Connectors

DFS connectors that support enrichment store scan results and anomaly data as files (Parquet/JSON) in cloud object storage. All 3 DFS connectors support enrichment.

No. Connector Logo Enrichment Support
1. Amazon S3 S3
2. Azure Datalake Storage (ABFS) ABFS
3. Google Cloud Storage (GCS) GCS