Pre-merge diffing.
Show what a model change will do to production output before it merges.
What counts as Pre-merge diffing?
Most data quality tools alert after a bad change has shipped. Pre-merge diffing runs the proposed model against a sample (or full copy) of the warehouse and surfaces the row-level difference between old and new output, attached to the pull request itself. Catches schema drift, value distribution changes, and unintended joins before they hit production dashboards.
4tools, grouped by primary cluster.
Datafold
Datafold
Pre-merge data diffing and column-level lineage — the tool that shifts data quality left into the pull request.
dbt-expectations
Metaplane (Datadog)
Open-source dbt package adding 50+ Great Expectations-style assertions as native dbt tests that run in your own warehouse.
Metaplane
Metaplane (Datadog)
ML-powered, no-code data observability for the dbt and warehouse stack with automatic column-level lineage — now Metaplane by Datadog.
Sifflet
Sifflet
EU-built full-stack data observability pairing ML-driven monitoring with an embedded catalog and field-level lineage.
Head-to-head, side by side.
Drill into a different capability.
How this list is built.
Inclusion here is one boolean on each tool's structured profile — if a tool you'd expect is missing, the field is recorded false or not yet verified, never an editorial call. See the methodology for how each field is sourced.