
Datafold
Datafold is a web-based data testing platform for teams that need to check data quality and schema changes.
What Datafold is
Datafold is a web-based data testing platform for teams that need to check data quality and schema changes. It supports schema migration tests and data quality checks, with tests written in SQL or YAML. Test execution supports both listed modes. Its database support spans cloud storage and analytics services as well as relational and data warehouse systems: Amazon S3, Azure Data Lake Storage, Athena, Azure Synapse Analytics, BigQuery, Databricks, Dremio, Google Cloud Storage, MySQL, MariaDB, Microsoft SQL Server, Netezza, Vertica, Oracle, Snowflake, PostgreSQL, Redshift, SAP HANA, Starburst, Teradata, and Trino. Founded in 2020, Datafold is offered on a paid basis, with pricing available on request and a 14-day trial. There is no free plan. The listed platform is web, so the entry is suited to users looking for browser-based data testing rather than a listed desktop or mobile app.
Good
- Checks both schema migrations and data quality
- Supports SQL and YAML test languages
- Test execution supports both listed modes
- Broad database support, including Snowflake and BigQuery
Watch out
- No free plan
- Pricing is available on request
Who it suits
Datafold suits teams that need schema migration tests and data quality checks across its supported databases. It is a fit for users comfortable writing tests in SQL or YAML.
Verdict
Datafold brings schema migration testing and data quality checks together, with support for a broad range of database systems. Consider the paid offering if its supported platforms and SQL or YAML test languages fit your workflow.
Plans and prices
From Datafold's own pricing page, checked 8 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Custom pricing | Priced on request | Pricing page redirects to contact us; no numeric price shown |
The facts
Each one read from Datafold's own pages, with the date it was checked.
What it does
- Beta availability
- The Data Knowledge Graph is in private beta and requires contacting Datafold to enable it.checked 8 Oct 2026
- Cloud providers
- Dedicated Cloud deployments are available on AWS, GCP, and Azure.checked 8 Oct 2026
- Compliance
- The Trust Center lists GDPR, HIPAA, and SOC 2 compliance statuses and provides access to security documentation, including a SOC 2 report and penetration test report.checked 7 Oct 2026
- Data Diff
- Data Diff compares data before and after pull requests and identifies changed rows and columns to catch value-level regressions before production.checked 7 Oct 2026
- Data diffs
- Datafold compares data before and after pull requests to identify value-level changes in rows and columns.checked 8 Oct 2026
- Data Knowledge Graph
- The Data Knowledge Graph collects lineage, business logic, usage, ontology, and organizational knowledge and serves it to AI agents via MCP.checked 8 Oct 2026
- Data quality
- Its data quality tools provide Data Diff in CI/CD, cross-system reconciliation, and proactive monitoring, with capabilities exposed via MCP.checked 7 Oct 2026
- Deployment
- Datafold is a web-based application offered as multi-tenant SaaS or dedicated cloud, including customer-hosted options.checked 8 Oct 2026
- Integrations
- The product page names Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, GitHub, and GitLab, and says Datafold integrates with 50+ data tools.checked 8 Oct 2026
- Intended users
- Datafold says it exists to empower data and analytics engineers and help data teams build reliable data products faster.checked 7 Oct 2026
- Knowledge graph
- The Data Knowledge Graph collects lineage, business logic, usage, and ontology, then serves this context to AI agents via MCP.checked 7 Oct 2026
- LLM controls
- Datafold says it can use LLM inference endpoints approved by a customer’s Security and IT team, including endpoints in AWS, GCP, Azure, Snowflake, or Databricks accounts.checked 7 Oct 2026
- Migration
- Its Data Migration Agent offers migrations with fixed price, timeline, and data parity guarantees.checked 8 Oct 2026
- Monitoring
- Datafold monitors data freshness, volume, and distribution to detect quality issues.checked 7 Oct 2026
- Monitoring and reconciliation
- Datafold supports freshness, volume, and distribution monitoring, plus cross-system reconciliation across databases.checked 8 Oct 2026
- Pricing availability
- The pricing URL redirects to the contact page, and the current site asks visitors to request a demo without showing a price.checked 7 Oct 2026
- Private deployment
- Datafold says it can run in a customer Virtual Private Cloud on AWS, GCP, or Azure so data stays inside the customer security perimeter.checked 8 Oct 2026
- Product
- Datafold builds specialized AI agents and tools for data engineering tasks including migrations, optimization, CI/CD, and data quality.checked 7 Oct 2026
- Purpose
- Datafold combines specialized AI agents, a context layer, and data quality tools to automate data engineering.checked 8 Oct 2026
- Security
- The Trust Center lists GDPR, HIPAA, and SOC 2 compliance statuses and provides access to security documents.checked 8 Oct 2026
- Support
- Support is available by email, in-app live chat, and a shared Slack channel arranged through an account executive.checked 8 Oct 2026
- Target users
- Datafold describes its platform as helping data teams and their coding agents ship higher-quality data faster and automate data engineering workflows.checked 8 Oct 2026
The company
- Company
- Datafold says it is an all-remote team; the opened About page does not state headquarters or founding year.checked 8 Oct 2026
- Founded
- 2020checked 23 Sep 2026
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