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RisingWave - Cloud-Native Streaming Database powered by SQL
RisingWave is a cloud-native streaming database that enables users to process and manage real-time data streams using SQL. It's designed for high throughput and low latency stream processing applications.
Rust
Added on 2025年6月11日7,870
Stars650
ForksRust
LanguageProject Introduction
Summary
RisingWave is an open-source, cloud-native streaming database designed for stream processing and management. It provides a SQL interface to query and manage continuous data streams, simplifying the development of real-time applications.
Problem Solved
Existing stream processing solutions are often complex, difficult to manage, and require specialized programming models. RisingWave simplifies real-time data processing by offering a familiar SQL interface and a cloud-native, database-like experience.
Core Features
SQL Interface
Interact with data streams using standard SQL, making it familiar for developers and analysts.
Cloud-Native Architecture
Built for cloud environments, leveraging Kubernetes for elasticity and scalability.
Stateful Stream Processing
Efficiently handle stateful computations on streams with built-in state management.
Tech Stack
Rust
C++
PostgreSQL Protocol
Kubernetes
Apache Kafka
Apache Pulsar
Amazon Kinesis
使用场景
RisingWave can be applied in various scenarios requiring real-time data processing and analytics:
Real-time IoT Data Analytics
Details
Ingest and process data from IoT devices in real-time for monitoring, anomaly detection, and predictive maintenance.
User Value
Gain immediate insights from device data to react quickly to critical events and optimize operations.
Real-time Business Intelligence Dashboards
Details
Build real-time dashboards and analytics applications for business intelligence, monitoring, and operational visibility.
User Value
Provide up-to-the-minute data to decision-makers, enabling faster and more informed business decisions.
Fraud Detection and Security Monitoring
Details
Monitor financial transactions, network activity, or user behavior streams to detect fraudulent patterns instantly.
User Value
Minimize losses and enhance security by identifying and responding to suspicious activities as they happen.
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