A fast and lightweight streaming SQL engine, 🚀 powered by ClickHouse

📄 Documentation   🚀 Live Demo   🌎 Timeplus

               

Why Use Timeplus Proton · How is it different from ClickHouse? . Demo Video · Deployment · What's Next · Integrations · Contributing · Need help?

Timeplus Proton is a stream processing engine and database. It is a fast and lightweight alternative to ksqlDB or Apache Flink, 🚀 powered by the libraries and engines in ClickHouse. It enables developers to solve streaming data processing, multi-stream JOINs, sophisticated incremental materialized views, routing and analytics challenges from Apache Kafka, Redpanda and more sources, and send aggregated data to the downstream streaming or database systems. Timeplus Proton is the core engine of Timeplus Enterprise.

💪 Why use Timeplus Proton?

1. Apache Flink or ksqlDB alternative. Timeplus Proton provides powerful stream processing functionalities, such as streaming ETL, tumble/hop/session windows, watermarks, incremental materialized views maintenance, CDC and data revision processing. In contrast to pure stream processors, it also stores queryable analytical/row based materialized views within Proton itself for use in analytics dashboards and applications.
2. Fast. Timeplus Proton is written in C++, with optimized performance through SIMD. For example, on an Apple MacBookPro with M2 Max, Timeplus Proton can deliver 90 million EPS, 4 millisecond end-to-end latency, and high cardinality aggregation with 1 million unique keys.
3. Lightweight. Timeplus Proton is a single binary (<500MB). No JVM or any other dependencies. You can also run it with Docker, or on an AWS t2.nano instance (1 vCPU and 0.5 GiB memory).
4. Powered by the fast, resource efficient and mature ClickHouse. Timeplus Proton extends the historical data, storage, and computing functionality of ClickHouse with stream processing. Thousands of SQL functions are available in Timeplus Proton. Billions of rows are queried in milliseconds.
5. Best streaming SQL engine for Kafka or Redpanda. Query the live data in Kafka or other compatible streaming data platforms, with external streams.

See our architecture doc for technical details and our FAQ for more information.

How is it different from ClickHouse?

ClickHouse is an extremely performant Data Warehouse built for fast analytical queries on large amounts of data. While it does support ingesting data from streaming sources such as Apache Kafka, it is itself not a stream processing engine which can transform and join streaming event data based on time-based semantics to detect patterns that need to be acted upon as soon as it happens. ClickHouse also has incremental materialized view capability but is limited to creating materialized view off of ingestion of blocks to a single table. Proton uses ClickHouse as a table store engine inside of each stream (alongside a Write Ahead Log and other data structures) and uses to unify real-time and historical data together to detect signals in the data. In addition, Proton can act as an advanced data pre-processor for ClickHouse (and similar systems) where the bulk of the data preparation and batching is done ahead of ingestion. See Timeplus and ClickHouse for more details on this.

🎬 Demo Video

2-minute short video👇. Check out the full video at YouTube.

DataTalksProtonHandbrake.mp4

⚡ Deployment

A single binary:

curl https://install.timeplus.com/oss | sh

Once the proton binary is available, you can run Timeplus Proton in different modes:

• Local Mode. You run proton local to start it for fast processing on local and remote files using SQL without having to install a full server
• Config-less Mode. You run proton server to start the server and put the config/logs/data in the current folder proton-data. Then use proton client in the other terminal to start the SQL client.
• Server Mode. You run sudo proton install to install the server in predefined path and a default configuration file. Then you can run sudo proton server -C /etc/proton-server/config.yaml to start the server and use proton client in the other terminal to start the SQL client.

For Mac users, you can also use Homebrew to manage the install/upgrade/uninstall:

brew install timeplus-io/timeplus/proton

Docker:

docker run -d --pull always -p 8123:8123 -p 8463:8463 --name proton d.timeplus.com/timeplus-io/proton:latest

Please check Server Ports to determine which ports to expose, so that other tools can connect to Timeplus, such as DBeaver.

Docker Compose:

The Docker Compose stack demonstrates how to read/write data in Kafka/Redpanda with external streams.

Timeplus Cloud:

Don't want to setup by yourself? Try Timeplus in Cloud

🔎 Usage

SQL is the main interface. You can start a new terminal window with proton client to start the SQL shell.

Note

You can also integrate Timeplus Proton with Python/Java/Go SDK, REST API, or BI plugins. Please check Integrations

In the proton client, you can write SQL to create External Stream for Kafka or External Table for ClickHouse.

You can also run the following SQL to create a stream of random 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);

-- Run the streaming SQL
SELECT device, count(*), min(temperature), max(temperature)
FROM devices GROUP BY device;

You should see data like the following:

┌─device──┬─count()─┬─min(temperature)─┬─max(temperature)─┐
│ device0 │    2256 │                0 │             99.6 │
│ device1 │    2260 │              0.1 │             99.7 │
│ device3 │    2259 │              0.3 │             99.9 │
│ device2 │    2225 │              0.2 │             99.8 │
└─────────┴─────────┴──────────────────┴──────────────────┘

⏩ What's next?

To see more examples of using Timeplus Proton, check out the examples folder.

To access more features, such as sources, sinks, dashboards, alerts, and data lineage, try Timeplus Enterprise locally or create a workspace on Timeplus Cloud.

What features are available with Timeplus Proton versus Timeplus Enterprise?

	Timeplus Proton	Timeplus Enterprise
Deployment	Single-node Docker image Single binary on Mac/Linux	Single node, or Cluster Kubernetes-based self-hosting, or Fully-managed cloud service
Data sources	Random streams External streams to Apache Kafka, Confluent Cloud, Redpanda Streaming ingestion via REST API (compact mode only)	Everything in Timeplus Proton External streams to another Timeplus Proton or Timeplus Enterprise deployment WebSocket and HTTP Stream NATS CSV upload Streaming ingestion via REST API (with API key and flexible modes) Hundreds of connectors from Redpanda Connect
Data destinations (sinks)	External streams to Apache Kafka, Confluent Cloud, Redpanda	Everything in Timeplus Proton External streams to another Timeplus Proton or Timeplus Enterprise deployment Slack Webhook Hundreds of connectors from Redpanda Connect
Support	Community support from GitHub and Slack	Enterprise support via email, Slack, and Zoom, with a SLA

🧩 Integrations

The following drivers are available:

• https://github.com/timeplus-io/proton-java-driver JDBC and other Java clients
• https://github.com/timeplus-io/proton-go-driver
• https://github.com/timeplus-io/proton-python-driver

Integrations with other systems:

• ClickHouse https://docs.timeplus.com/proton-clickhouse-external-table
• Docker and Testcontainers https://docs.timeplus.com/tutorial-testcontainers-java
• Sling https://docs.timeplus.com/sling
• Grafana https://github.com/timeplus-io/proton-grafana-source
• Metabase https://github.com/timeplus-io/metabase-proton-driver
• Pulse UI https://github.com/timeplus-io/pulseui/tree/proton
• Homebrew https://github.com/timeplus-io/homebrew-timeplus
• dbt https://github.com/timeplus-io/dbt-proton

Documentation

We publish full documentation for Timeplus Proton at docs.timeplus.com alongside documentation for Timeplus Enterprise.

We also have a FAQ for detailing how we chose Apache License 2.0, how Timeplus Proton is related to ClickHouse, and more.

Contributing

We welcome your contributions! If you are looking for issues to work on, try looking at the issue list.

Please see the wiki for more details, and BUILD.md to compile Timeplus Proton in different platforms.

Need help?

Please use GitHub Discussions to share your feedbacks or questions for Timeplus Proton.

For filing bugs, suggesting improvements, or requesting new features, open GitHub Issues.

To connect with Timeplus engineers or inquire about Timeplus Enterprise, join our Timeplus Community Slack.

Licensing

Proton uses Apache License 2.0. See details in the LICENSE.