Datafold
6.0#4 in data observability toolsWebAPISelf-hosted
VisitDatafold vs Metaplane
What both publish
| Fact | Datafold | Metaplane |
|---|---|---|
| Integrations | The product page names Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, GitHub, and GitLab, and says Datafold integrates with 50+ data tools. | Listed integrations include Snowflake, BigQuery, Redshift, ClickHouse, Databricks, dbt, Tableau, Looker, Slack, Microsoft Teams, PagerDuty, and Jira. |
| Monitoring | Datafold monitors data freshness, volume, and distribution to detect quality issues. | It supports volume, schema, freshness, uniqueness, nullness, statistical distribution, and custom SQL monitors. |
| Product | Datafold builds specialized AI agents and tools for data engineering tasks including migrations, optimization, CI/CD, and data quality. | Metaplane is an end-to-end data observability platform that catches data quality issues before they affect the business. |
| Security | The Trust Center lists GDPR, HIPAA, and SOC 2 compliance statuses and provides access to security documents. | Metaplane states that it complies with SOC 2, GDPR, and HIPAA, and that its SOC 2 report and Data Process Addendum are available upon request. |
| Support | Support is available by email, in-app live chat, and a shared Slack channel arranged through an account executive. | Free and Pro list email support; Enterprise includes premium support, a shared Slack channel, a customer success manager, and engineering time. |
Datafold plans
- Custom pricingPriced on request
Metaplane plans
- FreeFree
- EnterprisePriced on request
- Pro—
Pick Datafold if…
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.
Pick Metaplane if…
Metaplane suits teams that need to monitor data quality across warehouses and BI tools. It may also fit teams that want anomaly detection, lineage, or pull-request checks for data changes.