A simple collector that batches many small ClickHouse inserts into larger bulk inserts for improved performance.
ClickHouse-Bulk is a proxy service designed to optimize data insertion into Yandex ClickHouse databases. It addresses the performance issue of sending many small INSERT queries by collecting and batching them into larger, more efficient bulk inserts. This reduces network round trips and server load, making it ideal for high-volume data ingestion scenarios.
Developers and data engineers who are inserting high volumes of small, frequent data points into ClickHouse and need to improve ingestion performance and reduce server load.
It provides a simple, lightweight solution specifically for ClickHouse insert optimization without requiring changes to application code. Its configurability, support for multiple servers, and resilience features make it a robust choice for production data pipelines.
Collects many small inserts to ClickHouse and send in big inserts
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Groups multiple small INSERT queries into single bulk inserts, as demonstrated in the README where two INSERT statements are combined, significantly reducing network overhead and server load.
Allows fine-tuning via flush_count (row thresholds) and flush_interval (time intervals) in the configuration file, enabling adaptation to different data ingestion patterns.
Supports distributing inserts across multiple ClickHouse servers through the 'servers' array in the config, improving scalability and fault tolerance for high-volume scenarios.
Includes dump functionality to save unsent data during ClickHouse errors and automatic retry via dump_check_interval, enhancing data pipeline reliability as per the configuration options.
The batching mechanism with configurable flush intervals delays data insertion, which can be detrimental for real-time applications requiring immediate data availability after each insert.
Requires deploying and maintaining a separate proxy service, adding infrastructure complexity and creating a potential single point of failure if not properly managed.
As noted in the README, it primarily supports VALUES and TabSeparated formats, and lacks features for handling other ClickHouse operations or advanced ingestion scenarios like schema evolution.