queryq

Queryq is a modular query processing framework and domain-specific language intended for data analytics and integration. It provides a unified syntax for querying structured databases, semi-structured stores, and data streams, allowing users to express data retrieval and analysis without switching between separate query languages.

The Queryq language emphasizes declarative expressions, with support for selections, filters, joins, aggregations, window functions, and subqueries. It includes extensions for schema inference, type hints, and user-defined functions. Execution is separated from parsing, enabling optimizers to rewrite queries for efficiency across heterogeneous backends.

Key components include a parser, a cost-based optimizer, an execution engine, and a connectors layer with adapters to databases, data lakes, message buses, and file systems. The runtime supports streaming and incremental computation, with provenance metadata and fault tolerance features.

Common use cases are data warehousing, interactive analytics, data integration pipelines, and log analysis. The framework aims to simplify cross-store analytics by translating a single Queryq plan into backend-specific execution plans.

As a project with multiple community-driven implementations, queryq has seen varying maturity across connectors. Adoption focuses on flexibility and simplicity, balanced against the learning curve of a new query language and the overhead of optimizer tuning.