Pricing
Data observability pricing, planned to be transparent and self-serve
Every plan is planned to be paid and self-serve. No six-figure contract, no contact-sales gate to see a price. Built to start in minutes, no card required.
Starter
Small data teams, one warehouse
- 1 warehouse connection, read-only
- Table and column-level lineage
- Freshness monitoring
- Schema-change alerts
- Slack and email alerts
- 1 source, unlimited lineage maps
Team
Growing analytics and data-eng teams
- Everything in Starter
- Impact analysis before you ship
- Data anomaly detection
- Auto data catalog from lineage
- Multiple sources, unlimited team members
- Incident timeline
Scale
Data platform teams at scale
- Everything in Team
- Multiple warehouses
- Custom freshness SLAs
- Advanced anomaly models
- Audit log and SSO
- Priority support
Enterprise
Large orgs and regulated data
priced on request
- Custom connections
- Dedicated support
- Security review and DPA
- Guided onboarding
- Custom contract terms
Planned launch terms: 14-day money-back · no credit card to start · cancel anytime
Far below a six-figure contract
Enterprise observability and data-governance suites typically run 50,000 to 200,000 dollars or more per year, and a sales call just to see them. Datatrail is built to give data teams lineage, freshness monitoring, and impact analysis, self-serve and transparent, planned to start at 99 dollars per month.
Pricing FAQ
What you get and what it costs
Lineage is designed to map automatically in minutes from your query history, with no manual diagramming, no months-long rollout, and no need to annotate every model by hand. The first pass is built to surface your table and column flow, freshness state, and recent schema changes right away.
Yes. Datatrail traces a single column through every transformation, from its source table to the dashboards that use it. You can answer exactly what feeds a number and what would break if that column changed, not just which tables touch which tables.
Snowflake, BigQuery, Redshift, Postgres, and dbt, with read-only connections to query history and metadata. Datatrail parses real query logs, so it maps lineage past the dbt boundary and stays current even when someone writes ad-hoc SQL.
No. Datatrail does the mapping and watching, so your engineers spend time fixing and shipping rather than reverse-engineering dependencies in their head or hand-drawing diagrams that go stale. It makes a data team far more effective. It does not replace their judgment.