G2

Verified User in Hospital & Health Care

Mid-Market (51-1000 emp.)

9/22/2026

"Strong QA automation, but Git Sync needs work"

4/5

What do you like best about Datagaps DataOps Suite?

Datagaps lets us build reusable data-quality rules once and run them on a schedule across our SQL Server warehouse and Databricks Bronze, Silver, and Gold layers, which has replaced a lot of manual QA. Built-in profiling makes fill-rate and mapping gaps easy to spot, the Azure DevOps integration ties test results back to our stories, and the support team responds quickly when we hit configuration issues. Review collected by and hosted on G2.com.

What do you dislike about Datagaps DataOps Suite?

Git branch sync can be unreliable, with case-sensitivity renames and pipeline ID mismatches causing rework when promoting changes between branches. Connecting to multiple Azure SQL databases requires separate data sources because USE isn't supported, and frequently scheduled pipelines can drive up Databricks cluster costs unless dataflows are tuned. Clearer guidance on Git workflows and compute optimization would help. Review collected by and hosted on G2.com.

What problems is Datagaps DataOps Suite solving and how is that benefiting you?

We used to validate data warehouse and pipeline loads with manual, query-by-query checks, which was slow and hard to repeat. Datagaps lets us automate data-quality and reconciliation checks across our SQL Server warehouse and Databricks Bronze, Silver, and Gold layers, so issues like fill-rate and source mapping problems surface earlier. This has made our QA more consistent, traceable in Azure DevOps, and less dependent on manual effort. Review collected by and hosted on G2.com.