G2

Robert M.

Test Automation Architect

Small-Business (50 or fewer emp.)

10/13/2026

"Powerful Cross-Database Data Quality Checks with an Easy UI"

4.5/5

What do you like best about DataTrust?

* Disparate database dataset ingestion is very powerful. Being able to access datasets from sql, non sql, hierarchical databases for data validation and reconciliation in one tool speeds up data quality design and checks.

* the UI provides an easy and quick way to spin up and create data quality validations and Data quality reconciliations Across multiple database types

* Integration into email and slack is also very helpful for teams to get quick and accurate feedback on the quality of the data. Review collected by and hosted on G2.com.

What do you dislike about DataTrust?

* Limited parameterization reduces the ability to reuse some dataset ingestion components. Review collected by and hosted on G2.com.

What problems is DataTrust solving and how is that benefiting you?

2 very large areas of data quality both during development and in production.

* Database moves. Moving from Oracle database environment to Snowflake database and verify the data completely moved without error would have been almost impossible without Data Trust ingesting, processing the data (handling the different database types) given we had billions of rows of data that had to be checked character for character.

* Streaming processing verification. As the data moves from front end to back end systems Data Trust verifies both data validation and data completeness (data reconciliation) for the Data at rest repositories

As this processing happens in near real time having Data Trust check constantly helps to find errors and issues quickly and accurately. This is done in development as well as production. Review collected by and hosted on G2.com.