How it works
The data observability platform, end to end
Connect your warehouse read-only, let Datatrail map lineage from your query history and watch every table, trace any number to its source, and see the blast radius before a change ships. Here is exactly what happens at every step.
In one paragraph
Datatrail maps your data by connecting to your warehouse (Snowflake, BigQuery, Redshift, Postgres, dbt) with read-only access, reading your query history and metadata to map how data flows table to table and column to column, then letting you trace any number on a dashboard back to its source. It watches every table for freshness and schema drift, alerts the moment something goes stale, and lights the blast radius of a change, like the 12 downstream assets a single column feeds, before you ship it. You review each finding and act in your own warehouse. Datatrail is read-only to query history and metadata, and never moves or mutates your data.
Connect your warehouse, read-only
Grant read-only access to your query history and metadata on Snowflake (ACCESS_HISTORY and QUERY_HISTORY), BigQuery, Redshift, Postgres, or dbt. We request the minimum read scopes and never get write access, so the connection is fast and low-risk. Most teams finish in about 10 minutes.
- Read-only query history and metadata
- Snowflake, BigQuery, Redshift, Postgres, dbt
- No write access, ever
Datatrail maps the lineage
It parses your real query logs to map how data flows table to table and column to column, reads your dbt models, and watches every table for freshness and schema drift. The map builds itself from your query history and stays current even when someone writes ad-hoc SQL. The first pass runs as soon as the first source connects.
- Column-level lineage past dbt
- Watches every table
- Map builds itself, stays current
Trace any number to its source
Pick a column or a dashboard and see the whole path light up, source to model to exposure, with the count of every downstream asset that depends on it. Freshness and schema-change alerts route to Slack or email the moment a table breaches its SLA or a column changes upstream, so you hear it from Datatrail, not from someone reading a blank dashboard.
- Full source-to-dashboard path
- Freshness SLA and schema-drift alerts
- Routes to Slack or email
See impact before a change ships
Select a column you want to change and Datatrail lights the blast radius: every model and dashboard downstream that would break. You answer "if I drop this, what dies?" before the merge, not after. It is read-only decision support, and it never makes a change in your warehouse or mutates a row.
- Blast radius before you merge
- Acts in your own warehouse
- Read-only, never mutates data
The guardrail
Read-only by design, on purpose
We read your query history and metadata, we never copy or mutate a row, and we never change anything in your warehouse. It is the lowest-risk thing a data team can plug in.
Read-only access
We request the minimum read scopes, such as a read-only role on Snowflake ACCOUNT_USAGE or a read-only BigQuery viewer role. We cannot change anything in your warehouse.
We never move your data
No row-level ingestion, no copies, no writes, no changes to your tables. Datatrail reads metadata and query history to map lineage. It is an observer, not an actor.
Encrypted and revocable
Data is encrypted in transit and at rest, credentials are least-privilege and scoped, and you can revoke access at any time. See our security posture for the detail.
See it live
Watch the whole flow in one console
Read-only connection. Datatrail never moves or mutates your data.
See your data flow in minutes
Connect your warehouse read-only and watch lineage, freshness, and the blast radius of every change map themselves. Transparent pricing, no card to start.