Elementary
dbt-native data observability: anomaly tests, lineage, and Slack alerts.
About
Elementary is a dbt-native data observability platform for data and analytics engineers. An open-source dbt package plus CLI adds anomaly detection tests that run like native dbt tests, parses dbt artifacts into metadata tables in the warehouse, and generates a self-hosted observability report with lineage enriched by test results, sending actionable alerts to Slack and Teams.
The OSS core is Apache 2.0 and configuration lives as code inside the dbt project, so observability gets version control and code review like everything else. Elementary Cloud builds on the same foundation as a full Data and AI Control Plane with automated ML monitoring, column-level lineage from source to BI, a built-in catalog, and AI agents that scale reliability workflows. It is ranked among the top dbt packages with a community of thousands.
What it can do
- Anomaly detection and data quality tests as native dbt tests
- Warehouse-native metadata tables and lineage enriched with test results
- Self-hosted observability report plus Slack and Teams alerting
- Cloud tier adds ML monitoring, column lineage, and AI agents
Setup
Add the elementary dbt package to packages.yml, run dbt deps, wire the on-run-end hook, and use the edr CLI to generate reports and alerts.
Prerequisites
A dbt project on a supported warehouse; Slack or Teams for alerting.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 98; Trending score 74/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.