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elementary-data/elementary

Open-source CLI for dbt-native data observability that reads Elementary dbt package results to generate reports and send Slack and Teams alerts.

Open-source alternative to:Monte Carlo

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What is it?

Elementary OSS is a command-line tool for monitoring data quality inside dbt projects. It works together with the Elementary dbt package, which collects metadata, run artifacts and test results in your warehouse. The CLI reads that data to produce a data observability report, surface anomalies and failed tests, and track model and test performance over time.

Alerts can be sent to Slack and Microsoft Teams. The project supports anomaly detection as native dbt tests, along with a data quality dashboard, end-to-end lineage enriched with test results, a data catalog, and configuration managed as code in the dbt project. A dbt artifacts uploader saves run metadata as part of dbt runs.

The hosted Elementary Cloud offering adds automated ML monitors, column-level lineage from ingestion to BI, and AI agents. The open-source version covers the core report and alerting workflow.

Key features

  • 01Generates a data observability report from warehouse metadata and test results.
  • 02Sends anomaly and failed-test alerts to Slack and Microsoft Teams.
  • 03Provides anomaly detection tests that run as native dbt tests.
  • 04Tracks model and job run performance over time.
  • 05Offers end-to-end lineage enriched with test results.
  • 06Manages configuration as code inside the dbt project.

Use cases

  • Monitoring freshness, volume and schema issues in a dbt project on Snowflake, BigQuery or Redshift.
  • Getting Slack or Teams alerts when dbt tests fail or anomalies appear.
  • Tracing the downstream impact of a broken model during root cause analysis.
  • Reviewing model run times and test results across dbt runs over time.

Quick start

  1. 1

    Follow the quickstart guide to install and configure the Elementary dbt package and CLI

Things to know

  • It generates only the basic observability report; many advanced features are offered only in Elementary Cloud.
  • It requires the Elementary dbt package and a connected warehouse, so setup involves some configuration effort.

Topics

#data-observability#dbt#data-quality#data-lineage#data-pipelines#analytics-engineering#alerting#analytics-engineer#bigquery#data-analysis

FAQ

What is elementary?
Open-source CLI for dbt-native data observability that reads Elementary dbt package results to generate reports and send Slack and Teams alerts. Elementary OSS is a command-line tool for monitoring data quality inside dbt projects. It works together with the Elementary dbt package, which collects metadata, run artifacts and test results in your warehouse. The CLI reads that data to produce a data observability report, surface anomalies and failed tests, and track model and test performance over time.
Is elementary free to use? What license does it have?
elementary is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is elementary still maintained?
Actively maintained. The last commit to elementary was on Oct 13, 2026.
What can I use elementary for?
Monitoring freshness, volume and schema issues in a dbt project on Snowflake, BigQuery or Redshift. Getting Slack or Teams alerts when dbt tests fail or anomalies appear. Tracing the downstream impact of a broken model during root cause analysis. Reviewing model run times and test results across dbt runs over time.
How do I install elementary?
Follow the quickstart guide to install and configure the Elementary dbt package and CLI
Where can I get elementary?
The source code and installation instructions are on GitHub: https://github.com/elementary-data/elementary

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