DataTrail

Pricing

Data observability pricing, transparent and self-serve

Every plan is paid and self-serve. No six-figure contract, no contact-sales gate to see a price. Built to start in minutes, no card required.

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Starter

Small data teams, one warehouse

$59 /mo

Get started
  • 1 warehouse connection, read-only
  • Table and column-level lineage
  • Freshness monitoring
  • Schema-change alerts
  • Slack and email alerts
  • 1 source, unlimited lineage maps
Most popular

Team

Growing analytics and data-eng teams

$179 /mo

Get started
  • 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

$479 /mo

Get started
  • Everything in Team
  • Multiple warehouses
  • Custom freshness SLAs
  • Advanced anomaly models
  • Audit log and SSO
  • Priority support

Enterprise

Large orgs and regulated data

$999 /mo

Get started
  • Custom connections
  • Dedicated support
  • Security review and DPA
  • Guided onboarding
  • Custom contract terms

Billed monthly or yearly · 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, starting at 59 dollars per month billed yearly.

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.