Recce: Your data change management toolkit
Whether you’re the author of a pull request or the one reviewing it, you’ve got a tough job: figuring out what changed, verifying that the PR does what it’s supposed to, and making sure nothing breaks in production. In large or business-critical dbt projects, this can be a slow, frustrating process. That’s why we built Recce - an open-source toolkit that’s here to make your data modeling validation and pull request (PR) reviews a breeze.
What is Recce?
Recce (pronounced “reh-kee”, short for “reconnaissance”) is a suite of change management tools designed to help you compare dbt environments, assess data impacts, and streamline your PR reviews. Recce gives you visibility into the effects of your data modeling changes before they hit production. With Recce, you can take two dbt environments, such as dev and prod, and compare them using the suite of diff tools.
Your diffing toolkit
With Recce you’re able to validate your data modeling changes against a known-good baseline, comparing datasets before and after your modifications, in a risk-free environment. And there’s a diff for every occasion.
Lineage DAG diff
Start from the zone of impact of your changes, and see which models have been modified, added, and removed. Unlike the dbt docs lineage DAG, which only shows you the current state of the DAG, Recce shows you how the DAG differs from both before and after your changes.
Data profile diff and value diff
Perform holistic checks by diffing the data profile stats for your development branch, then check the percentage of values matching for each column in a model.
Query diff
If something needs further investigation, drill down and query the data. One query will run on both environments, and you’ll be able to see the difference on a row-by-row basis. Enable change-only view to see just what’s changed.
Schema and row count
In addition to the above diffs, you can also check the schema and row count, just to be sure you didn’t lose any data, or an important column.
You’ve been hard at work, time to show it
As you create validations in Recce, you can add them to your curated checklist with notes about what you found, and re-re-run checks if the data changes.
Once you’ve validated your changes, it’s time to share your work. Recce lets you export your checks directly into your PR comment template, so you can provide clear, proof-of-correctness evidence. You can copy key notes, grab a screenshot of the validation results, and include only the relevant details, keeping your PR comment all-signal, no noise.
For reviewers, this means they can quickly see the queries and results of your data spot-checks, making it easy to assess the impact of your changes. With all the context at hand, they can either ask for further investigation or confidently approve the PR.
## Getting started with Recce
Ready to revolutionize your data review process? Recce is open-source and easy to integrate into your workflow.
Recce OSS is available on GitHub. Follow the instructions in our Getting Started guide to start using Recce to validate your data modeling changes.
- GitHub: DataRecce/Recce
- Docs: DataRecce.io/docs
- Discord: Recce Community
Try Recce Online
If you want to try Recce out without having to install, check out our demo instance.
Demo
The demo PR makes a simple change to the dbt’s Jaffle Shop project and changes how customer_lifetime_value (CLV) is calculated by fixing the calculation to only evaluate completed orders.
The expectation from this change is that CLV will be reduced overall, and that this will also impact the customer segments downstream model. With that in mind, see if you can determine if the if the PR has any issues by checking the data in Recce:
- The PR: https://github.com/DataRecce/jaffle_shop_duckdb/pull/1
- Recce Demo instance: https://pr1.cloud.datarecce.io/
Hint: Run a Profile Diff, then a Query Diff, on the customers model. Then check for downstream impact.
For even more details on using Recce to perform data impact assessment, check out our hands-on guide.
Start shipping data models with confidence with Recce
Data modeling changes shouldn’t feel like a gamble. Whether you’re the one writing the PR or the one reviewing it, you need confidence that what’s changing is actually what was intended —without breaking production. Recce gives you the tools to compare environments, validate your data, and surface meaningful insights, all while keeping PR comments focused and actionable.
If you’re tired of slow QA cycles, silent data errors, and bloated CI pipelines, it’s time to give Recce a shot.