Curvine is a distributed caching system implemented in Rust, featuring high concurrency, high throughput, low latency, and low resource consumption. Unlike KV caches like Redis or TiKV, Curvine exclusively provides file caching capabilities. It is not a storage system but rather a caching layer - data persistence still relies on underlying file systems or object storage systems for support.
In practical applications, what scenarios are suitable for Curvine acceleration?
As shown in the figure above, Curvine is designed for the following five core scenarios:
Accelerating intermediate data processing in big data shuffle operations
Caching hot table data for faster big data analytics
Boosting AI training efficiency through dataset caching
Accelerating model file distribution via caching layer
Cross-cloud data caching to mitigate performance bottlenecks of dedicated cloud connections
These use cases are just the beginning. In simple terms, Curvine fundamentally addresses: The growing conflict between escalating computational demands and the I/O bottlenecks of distributed cache systems.
