As officially announced by the Apache Software Foundation, we are thrilled to share that Apache Fluss has graduated from the Apache Incubator to become a Top Level Project (TLP). The project's graduation proposal received unanimous approval…
Part 1 and Part 2 built up everything you need to know about how tiering behaves: the mental model, the dials, the queue dynamics, the scale-out story. This part is about what to do with all of that. What breaks at runtime, and which of tho…
If you're new to Fluss, the lake-tiering story is one of those topics where every explanation seems to assume you already know how it works. This three-part walkthrough aims to bring some clarity to the confusing parts of the system, and to…
Apache Kafka's "column pruning" is actually pseudo-pruning. All fields still cross the network, and clients discard unwanted ones after the fact. Apache Fluss redesigns the storage format, server-side read path, and write-side batching stra…
If you maintain a data system that only speaks Java, you will eventually hear from someone who doesn't. A Python team building a feature store. A C++ service that needs sub-millisecond writes. An AI agent that wants to call your system thro…
We are excited to announce the release of fluss-rust clients 0.1.0, the first official release of the Rust, Python, and C++ clients for Apache Fluss. This 0.1.0 release represents the culmination of 210+ commits from the community, deliveri…
🌊 We are excited to announce the official release of Apache Fluss (Incubating) 0.9! This release marks a major milestone for the project. Fluss 0.9 significantly expands Fluss’s capabilities as a streaming storage system for real-time anal…
Fraud detection is a mission-critical capability for businesses operating in financial services, e-commerce, and digital payments. Detecting suspicious transactions in real time can prevent significant losses and protect customers. This blo…
As software and data engineers, we've witnessed Apache Iceberg revolutionize analytical data lakes with ACID transactions, time travel, and schema evolution. Yet when we try to push Iceberg into real-time workloads such as sub-second stream…
🌊 We are excited to announce the official release of Apache Fluss (Incubating) 0.8! This is our first release under the incubator of the Apache Software Foundation, marking a significant milestone in our journey to provide a robust streami…
Apache Fluss is a streaming data storage system built for real-time analytics, serving as a low-latency data layer in modern data Lakehouses. It supports sub-second streaming reads and writes, storing data in a columnar format for efficienc…
Traditional streaming data pipelines often need to join many tables or streams on a primary key to create a wide view. For example, imagine you’re building a real-time recommendation engine for an e-commerce platform. To serve highly person…