DataSQRL/sqrl

This system is a data engineering framework that compiles SQL-based data pipeline definitions into executable applications. It translates logical query plans into physical execution plans for diverse backends, including Flink for streaming, Postgres and DuckDB for relational storage, and Kafka for logging. The system provides a CLI for project scaffolding and compilation, a server for GraphQL/REST APIs, and supports flexible schema handling for various data formats.

This period focused on a comprehensive refactoring of the query planner and execution engine architecture. The team removed legacy SQL parsing, GraphQL, and database-specific implementations to make way for a modular, extensible engine abstraction that supports Flink, Postgres, and Kafka. Additionally, the codebase introduced flexible schema handling, dialect-specific function transformations, and improved test coverage for the new planning infrastructure.

60 changes

The period focused on a comprehensive architectural overhaul of the SQRL planner and CLI, introducing a DAG-based query planner, flexible schema handling, and a modular preprocessing pipeline. This structural refactoring was accompanied by the addition of SQL dialect support for Postgres, DuckDB, and Snowflake, alongside extensive integration and unit test coverage for the new components.

81 changes

This period focused on expanding test coverage across the SQL planner, server, and integration layers, including new tests for Flink, DuckDB, and PostgreSQL features. Concurrently, the server module was refactored to support documentation strings and enhanced with request tracing and GraphQL query metrics for improved observability.

20 changes

DataSQRL/sqrl was measured the same way every project in this corpus was: the same rubric, at a pinned commit, with the result published in full. Point the surveyor at a repository you know and see whether you agree with it.