Managed Connectors
The Kafka and the ClickHouse connectors are built and updated by the GlassFlow team.
High Performance
The connectors are created for optimal throughput and native support.
Clean Data
You can dedupe and join Kafka streams within GlassFlow before ingesting to ClickHouse. Auto retries make sure your data is up-to-date.
Comparison
See in detail how GlassFlow performs compared to alternative solutions
Open source
Quick to start
Low maintanance
Latency
Built-in stateful processing
Error handling
Transformation support
Very low
Built in retries with backoff
Advanced
ClickHouse Kafka Table Engine
Very low
Basic
Limited
Clickpipes for
Kafka
Very low
Built-in retries and monitoring
Basic
Go
Service
Very low

Learn how to stream data from Kafka to ClickHouse using Kafka Engine, ClickPipes, or Kafka Connect. Understand when to use each.
From Kafka to ClickHouse: Get all details.
How does it work?
Supports multiple Kafka topics and partitions
GlassFlow natively supports consuming from multiple Kafka topics and partitions in parallel, ensuring high-throughput and scalable ingestion. It automatically handles partition assignment, offset tracking, and rebalancing behind the scenes. This allows you to build unified pipelines that process data from various sources without manual coordination.
Adjustable waiting times for optimal throughput
GlassFlow lets you configure wait times between batch reads from Kafka, allowing you to control how often data is flushed downstream. By adjusting this interval, you can optimize the trade-off between latency and throughput based on your workload. This flexibility helps maximize performance without overwhelming downstream systems like ClickHouse.
Configurable batch sizes
GlassFlow allows you to set configurable batch sizes for reading and processing data from Kafka, tailoring the amount of data handled in each batch. This helps balance between processing efficiency and memory usage, adapting to different workload demands. By tuning batch sizes, you can optimize pipeline throughput and reduce latency based on your system’s capacity and performance goals.
Frequently asked questions
Feel free to contact us if you have any questions after reviewing our FAQs.