What is SQLFlow?
SQLFlow is a stream processing tool that simplifies building data pipelines by modeling them as SQL queries using the DuckDB SQL dialect. It allows users to express entire stream processing workflows—including ingestion, transformation, and enrichment—as a single SQL statement and configuration file. This approach leverages familiar SQL syntax to reduce complexity and accelerate development for real-time data processing tasks.
The tool is designed for high performance, capable of processing tens of thousands of events per second on a single machine with low memory overhead. It is built on Python, DuckDB, Arrow, and the Confluent Python Client, integrating with the DuckDB ecosystem to support various data formats such as parquet, csv, json, and iceberg, and read data from Kafka. SQLFlow empowers developers to create efficient stream processing applications without extensive coding, making it accessible for handling large-scale event-driven data.
Features
- SQL-Based Processing: Express stream processing pipelines as SQL queries using DuckDB dialect
- High Performance: Process tens of thousands of events per second on a single machine with low memory overhead
- DuckDB Integration: Leverage DuckDB ecosystem tools and libraries for building applications
- Multi-Format Support: Handle data in parquet, csv, json, and iceberg formats
- Kafka Compatibility: Read data from Kafka for real-time stream ingestion
Use Cases
- Real-time data transformation from Kafka streams
- Building event-driven data pipelines for analytics
- Enriching streaming data with SQL-based operations
- Processing high-volume event logs efficiently
- Creating data ingestion workflows for various formats
