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https://github.com/quarylabs/quary
Open-source BI for engineers
https://github.com/quarylabs/quary
analytics big-data business-intelligence data-modeling elt
Last synced: 4 months ago
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Open-source BI for engineers
- Host: GitHub
- URL: https://github.com/quarylabs/quary
- Owner: quarylabs
- License: apache-2.0
- Created: 2024-02-20T23:33:53.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-29T08:47:07.000Z (4 months ago)
- Last Synced: 2024-10-29T09:55:21.153Z (4 months ago)
- Topics: analytics, big-data, business-intelligence, data-modeling, elt
- Language: Rust
- Homepage: https://www.quary.dev
- Size: 105 MB
- Stars: 2,178
- Watchers: 12
- Forks: 51
- Open Issues: 41
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Quary
Business Intelligence for Engineers 🅀
[](https://www.quary.dev/)
[](https://join.slack.com/t/quarylabs/shared_invite/zt-2dlbfnztw-dMLXJVL38NcbhqRuM5gUcw)
[](https://www.ycombinator.com/companies/quary)
[](https://github.com/quarylabs/quary)
With Quary, engineers can:
- 🔌 Connect to their Database
- 📖 Write SQL queries to transform, organize, and document tables in a database
- 📊 Create charts, dashboards and reports (in development)
- 🧪 Test, collaborate & refactor iteratively through version control
- 🚀 Deploy the organised, documented model back up to the database
View the [documentation](https://www.quary.dev/docs).
## 🗃️ Supported Databases
## 🏗️ Asset Types in Quary
Define and manage the following asset types as code:
- **Sources:** Define the external data sources that feed into Quary, such as database tables, flat files, or APIs (with DuckDB).
- **Models:** Transform raw data from sources into analysis-ready datasets using SQL, this lets engineers split complex queries into atomic components.
- **Charts:** Create visual representations of your data using SQL.
- **🚧 Dashboards (WIP):** Combine multiple charts into a single view, allowing engineers to monitor and analyze data in one place.
- **🚧 Reports (WIP):** Create detailed reports to share insights and findings with your team or stakeholders.
## 🚀 Getting Started
### Installation
Quary is a VSCode Extension (Interface) & Rust-based CLI (Core)
#### Extension
The VSCode extension can be installed [here](https://marketplace.visualstudio.com/items?itemName=Quary.quary-extension). Note that it depends on the CLI being installed.
#### CLI
#### Homebrew installation
```
brew install quarylabs/quary/quary
```
#### Linux/Mac through curl
Quary can be installed using curl on Linux/Mac using the following command:
```shell
curl -fsSL https://raw.githubusercontent.com/quarylabs/quary/main/install.sh | bash
```
#### Other installations
Other builds are available in the [releases page](https://github.com/quarylabs/quary/releases/latest) to download.
### Usage
Once installed, a sample project can be created and run as follows:
```shell
mkdir example # create an empty project folder
cd example
quary init # initialize DuckDB demo project with sample data
quary compile # validate the project structure and model references without database
quary build # build and execute the model views/seeds against target database
quary test -s # run defined tests against target database
```
🅀 Community
[Join our Slack channel](https://join.slack.com/t/quarylabs/shared_invite/zt-2dlbfnztw-dMLXJVL38NcbhqRuM5gUcw), for help, ideas, and discussions.
## Support
If you run into any problems using Quary, please let us know. We want Quary to be easy-to-use, so if you are getting
confused, it is our fault, not yours. [Create an issue](https://github.com/quarylabs/quary/issues) and we'll be happy to
help you out.
### Check out our other projects
[SQRUFF](https://github.com/quarylabs/sqruff), a compact, high-speed SQL linter, engineered with Rust efficiency.