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Fluss: Streaming Storage for Real-time Analytics
Fluss is a streaming storage built for real-time analytics, designed to handle high-throughput data ingestion and low-latency queries.
Java
Added on 2025年6月27日1,228
Stars329
ForksJava
LanguageProject Introduction
Summary
Fluss is an open-source streaming storage system developed by Alibaba, optimized specifically for real-time analytical processing directly on streaming data without requiring separate batch layers.
Problem Solved
Existing storage solutions often struggle to provide both high-volume streaming ingestion and low-latency analytical queries on the same data store efficiently, leading to complex data pipelines and increased operational overhead. Fluss aims to unify these capabilities.
Core Features
High-Throughput Data Ingestion
Ingest high volumes of streaming data with minimal latency, supporting various protocols.
Low-Latency Real-time Queries
Provides sub-second query response times for analytical workloads on recent data.
Durability and Fault Tolerance
Ensures data safety and availability through replication and fault tolerance mechanisms.
Tech Stack
Java
Scala
Distributed Systems
Networking
Data Structures
Use Cases
Fluss is suitable for a wide range of applications where real-time access and analysis of continuous data streams are critical.
Real-time Monitoring and Anomaly Detection
Details
Process incoming logs or sensor data in real-time to detect anomalies, system health issues, or performance bottlenecks instantly.
User Value
Reduce detection latency and enable faster response to critical events.
Fraud Detection and Behavioral Analytics
Details
Analyze user clickstream data or transaction logs in real-time to personalize user experiences, detect fraudulent activities, or make immediate business decisions.
User Value
Improve accuracy and speed of detection, enhancing security and user engagement.
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