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apache/fluss

Apache Fluss is a streaming storage built for real-time analytics.

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README.md

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<a href="https://fluss.apache.org/docs/">Documentation</a> | <a href="https://fluss.apache.org/docs/quickstart/flink/">QuickStart</a> | <a href="https://fluss.apache.org/community/dev/ide-setup/">Development</a>

## What is Apache Fluss?

Apache Fluss is a streaming storage built for real-time analytics & AI which can serve as the real-time data layer for Lakehouse architectures.

It bridges the gap between **data streaming** and **data Lakehouse** by enabling low-latency, high-throughput data ingestion and processing while seamlessly integrating with popular compute engines like **Apache Flink** and
**Apache Spark**, with StarRocks coming soon.

**Fluss (German: river, pronounced `/flus/`)** enables streaming data continuously converging, distributing and flowing into lakes, like a river 🌊

## Features

- **Sub-Second Data Freshness**: Continuous ingestion and immediate availability of data enable low-latency analytics and real-time decision-making at scale.
- **Streaming & Lakehouse Unification**: Streaming-native storage with low-latency access on top of the lakehouse, using tables as a single abstraction to unify real-time and historical data across engines.
- **Columnar Streaming**: Based on Apache Arrow it allows database primitives on data streams and techniques like column pruning and predicate pushdown. This ensures engines read only the data they need, minimizing I/O and network costs.
- **Compute–Storage Separation**: Stream processors focus on pure computation while Fluss manages state and storage, with features like deduplication, partial updates, delta joins, and aggregation merge engines.
- **ML & AI–Ready Storage**: A unified storage layer supporting row-based, columnar, vector, and multi-modal data, enabling real-time feature stores and a centralized data repository for ML and AI systems.
- **Changelogs & Decision Tracking**: Built-in changelog generation provides an append-only history of state and decision evolution, enabling auditing, reproducibility, and deep system observability.

## Building

Prerequisites for building Apache Fluss:

- Unix-like environment (we use Linux, Mac OS X, Cygwin, WSL)
- Git
- Maven (we require version >= 3.8.6)
- Java 11

```bash
git clone https://github.com/apache/fluss.git
cd fluss
./mvnw clean package -DskipTests
```

Apache Fluss is now installed in `build-target`. The build command uses Maven Wrapper (`mvnw`) which ensures the correct Maven version is used.

## Contributing

Apache Fluss is open-source, and we’d love your help to keep it growing! Join the [discussions](https://github.com/apache/fluss/discussions),
open [issues](https://github.com/apache/fluss/issues) if you find a bug or request features, contribute code and documentation,
or help us improve the project in any way. All contributions are welcome!

## License

Apache Fluss project is licensed under the [Apache License 2.0](https://github.com/apache/fluss/blob/main/LICENSE).

Repository info

Default branch: main
Latest version: v1.0.0
Created: 2024-10-31
Last activity: 2026-10-14
License: Apache-2.0
Open issues: 1.1k
Watchers: 36

Topics

big-data fluss hacktoberfest lakehouse real-time-analytics streaming

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