# Datafold

**Source:** https://geo.sig.ai/brands/datafold  
**Vertical:** Developer Tools  
**Subcategory:** General  
**Tier:** Challenger  
**Website:** datafold.com  
**Last Updated:** 2026-04-15

## Summary

Data observability platform for automated pipeline change validation; Column-level lineage and Datadiff for dbt engineers to detect data quality regressions before production impact.

## Company Overview

Datafold is a data observability and data quality testing platform that helps data engineering teams automatically detect data quality regressions, schema changes, and anomalies in their data pipelines before they impact downstream analytics and business decisions. Founded in 2020 by Gleb Mezhanskiy and Alexey Astafyev and headquartered in San Francisco, Datafold was built by data engineers who experienced the pain of data quality issues at scale and raised approximately $20 million to build a dedicated solution.\n\nDatafold's core product is Column-level Lineage and Datadiff — automatically comparing data between pipeline versions or time periods to surface when a code change causes unexpected shifts in data distributions, row counts, or metric values. This "data diff" capability enables data engineers to review the actual impact of their dbt or SQL pipeline changes on downstream data before merging, similar to how code review shows code diffs. The platform integrates with dbt (the dominant SQL transformation tool), Airflow, and major cloud data warehouses (Snowflake, BigQuery, Redshift).\n\nIn 2025, Datafold competes in the data observability market against Monte Carlo (enterprise data observability), Great Expectations (open-source data testing), Soda (data quality), and dbt's built-in testing capabilities. The data quality space has matured as organizations recognize that bad data costs more than bad code — pipeline failures that corrupt analytics silently are particularly damaging. Datafold's differentiation is its automated data diffing for pipeline change validation, which is more proactive than anomaly detection-based tools. The 2025 strategy focuses on the dbt ecosystem where Datafold has strong traction, expanding CI/CD pipeline integrations, and building AI-powered root cause analysis for data quality issues.

## Frequently Asked Questions

### What is Datafold?
Datafold is a developer tools company that automates critical data engineering workflows for modern data teams. The platform helps teams deliver reliable data products faster by automating data migrations, code testing and review, and monitoring and observability.

### What products and services does Datafold offer?
Datafold offers automated data testing, data migration automation, data quality monitoring, code review automation, and a data observability platform. These tools form a unified data quality platform that spans from testing to monitoring capabilities.

### Who is Datafold designed for?
Datafold is designed for modern data teams and data engineers who need to manage data quality, perform data migrations, and ensure reliable data products. The company has introduced new pricing for broader accessibility to serve more teams.

### When was Datafold founded?
Datafold was founded in 2020 by Gleb Mezhanskiy and Alex Morozov. The company was part of Y Combinator's Winter 2020 (W20) batch.

### Where is Datafold located?
Datafold is headquartered in San Francisco, California.

### How much funding has Datafold raised?
Datafold has raised $27.3 million in total funding, including a $20 million Series A round in November 2021 led by NEA (New Enterprise Associates). Other investors include Amplify Partners, Jagdeo Ventures, S2 Capital, BT Growth Capital, and Y Combinator.

### What are Datafold's key achievements?
Datafold has raised $27.3M in total funding and completed a $20M Series A round led by NEA in November 2021. The company has evolved from a testing-focused solution to a unified data quality platform with comprehensive monitoring capabilities.

### What is Datafold's approach to data quality management?
Datafold dramatically speeds up data quality management by automating the monitoring of analytical data and critical data engineering workflows. The platform provides a unified approach that covers testing, code review, migrations, and observability.

### Who founded Datafold?
Datafold was founded by Gleb Mezhanskiy and Alex Morozov in 2020. The company was part of Y Combinator's Winter 2020 batch.

### What are the latest developments at Datafold?
Datafold recently expanded from testing capabilities to a unified data quality platform that includes monitoring and observability features. The company has also introduced new pricing to make their platform accessible to a broader range of data teams.

## Tags

api-first, b2b, developer-tools, platform, saas, startup

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*Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-15.*