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Modern BI platform for governed data modeling and dashboards
Quary
Engineers' toolkit for building, testing, and deploying data models
Quary lets engineers connect to databases, define sources, write modular SQL models, test via version control, and deploy documented data assets—all from a VSCode extension and Rust CLI.
Overview
Highlights
SQL‑first data modeling with version‑controlled assets
Integrated testing and refactoring workflow
VSCode UI paired with a fast Rust CLI
Support for multiple databases and DuckDB‑based sources
Pros
- Native SQL workflow aligns with engineers' skill set
- Version‑control friendly enables collaborative development
- Cross‑platform CLI simplifies installation
- Extensible asset types (sources, models, charts)
Considerations
- Dashboard and report features still in development
- Limited to databases supported by underlying adapters
- Requires VSCode for full UI experience
- Learning curve for asset‑as‑code paradigm
Managed products teams compare with
When teams consider Quary, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Data teams that prefer code‑first BI pipelines
- Engineers building reproducible data models within CI/CD
- Organizations needing lightweight, self‑hosted analytics
- Projects that already use VSCode as primary IDE
Not ideal when
- Teams requiring out‑of‑the‑box visual dashboarding
- Non‑technical business users without SQL expertise
- Environments lacking VSCode or Rust runtime
- Large enterprises needing enterprise‑grade BI licensing
How teams use it
Transform raw event logs into clean analytics tables
Engineers split complex ETL logic into modular SQL models, versioned and tested automatically.
Create a sales performance chart for quarterly review
SQL‑driven chart generated within VSCode, ready to embed in reports.
Validate data quality before production deployment
Automated tests catch schema or value anomalies, preventing faulty data releases.
Deploy documented data models to production database
CLI builds and pushes transformed tables, ensuring reproducible deployments.
Tech snapshot
Rust74%
TypeScript24%
CSS1%
JavaScript1%
Shell1%
Makefile1%
Frequently asked questions
What databases does Quary support?
Quary works with any database that has a compatible driver; out‑of‑the‑box support includes DuckDB, PostgreSQL, MySQL, and others via standard SQL connections.
Do I need both the VSCode extension and CLI?
The extension provides the UI; the CLI performs all core operations. The extension depends on the CLI, so installing both is recommended.
How are tests defined and run?
Tests are written as SQL assertions in model files and executed with `quary test`, integrating with version control.
Is Quary suitable for production workloads?
Yes, models can be compiled, built, and deployed to target databases, and the workflow supports CI/CD pipelines.
Where can I get help or contribute?
Join the community Slack, file issues on GitHub, or submit pull requests; the project is Apache‑2.0 licensed.
Project at a glance
Active- Stars
- 2,355
- Watchers
- 2,355
- Forks
- 59
LicenseApache-2.0
Repo age1 year old
Last commit3 days ago
Primary languageRust
Last synced yesterday