Documentation Index Fetch the complete documentation index at: https://mintlify.com/timeplus-io/proton/llms.txt
Use this file to discover all available pages before exploring further.
Timeplus Proton Documentation Learn how to build blazing-fast stream processing pipelines with the fastest SQL engine in a single binary. No JVM. No Zookeeper. Just speed, control, and scale.
Quick Start Get Proton running in seconds
Install Proton
Install Proton with a single command: curl https://install.timeplus.com/oss | sh
Or use Docker: docker run -d -p 8123:8123 -p 8463:8463 --name proton \ d.timeplus.com/timeplus-io/proton:latest
Start the Server
Launch Proton server and client: proton server # In one terminal proton client # In another terminal
On Mac, you can also use Homebrew: brew install timeplus-io/timeplus/proton
Run Your First Query
Create a stream and query real-time data: -- Create a stream with random data CREATE RANDOM STREAM devices( device string default 'device' || to_string( rand ()% 4 ), temperature float default rand ()% 1000 / 10 ); -- Query streaming data SELECT device, count ( * ), avg (temperature) FROM devices GROUP BY device;
┌─device──┬─count()─┬─avg(temperature)─┐ │ device0 │ 2256 │ 49.8 │ │ device1 │ 2260 │ 50.2 │ │ device3 │ 2259 │ 49.5 │ │ device2 │ 2225 │ 50.1 │ └─────────┴─────────┴──────────────────┘
Explore by Topic Deep dive into Proton’s capabilities
Architecture Understand how Proton processes streams with ClickHouse-powered performance
Streams Learn about streams, the core abstraction for real-time data processing
Windows Master tumbling, hopping, and session windows for time-based aggregations
Kafka Integration Connect to Kafka, Redpanda, and other streaming platforms with external streams
Materialized Views Build real-time dashboards with incrementally maintained aggregations
SQL Reference Complete SQL syntax reference for stream processing commands
Use Cases See what you can build with Proton
Real-Time ETL Build streaming data pipelines that transform and route data in real-time
Telemetry Pipeline Process logs, metrics, and traces with in-pipeline aggregation and alerting
AI Feature Pipeline Compute real-time features for machine learning models with low latency
Change Data Capture Stream database changes and maintain real-time replicas
Why Proton? The fastest, simplest stream processing engine
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Blazing Fast 90M events/sec with 4ms latency on commodity hardware. Written in C++ with SIMD optimizations.
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Lightweight Single binary under 500MB. No JVM, no Zookeeper. Runs on t2.nano with 0.5GB RAM.
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Native Kafka Support Query Kafka topics directly with external streams. No data copying required.
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SQL for Everything Streaming ingestion, JOINs, windows, materialized views, UDFs—all with standard SQL.
Ready to Get Started? Install Proton in seconds and start building real-time data pipelines with SQL
Start Building → Community & Support Get help and connect with other Proton users
GitHub Star the repo, report issues, and contribute to development
Slack Community Join our community Slack to ask questions and share your projects
Examples Browse real-world examples and templates to get started faster
