SQLY is a YAML-based query language inspired by JQL, Kusto, and DQL. It is designed for querying structured and semi-structured data efficiently.
🔹 Basics
Learn how to write simple SQLY queries, including select, from, where, order_by, and group_by.
Explore complex filtering, logical operators, sorting, and aggregations.
Use subqueries to fetch results dynamically within a query.
Utilize CTEs to structure queries for better readability and performance.
Perform ranking, running totals, and moving averages using window functions.
Handle hierarchical data, such as employee relationships or category trees.
Perform fuzzy searches and text matching in large datasets.
Work with geospatial data to find points within a radius, bounding boxes, and distances.
Integrate predictive models for forecasting and anomaly detection within queries.
Filter and manipulate JSON fields and array data types.
Define and use custom functions to extend SQLY’s capabilities.
Learn techniques to optimize query execution and improve efficiency.
Enable query tracing, logging, and error handling for efficient debugging.
Explore custom functions, external data sources, and event-driven triggers.
To start using SQLY, check out the Basics section and explore examples.
Contributions are welcome! Feel free to submit PRs or issues for improvements.
This project is licensed under the MIT License.
