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The new IO model and scheduler provide fine-tuned balancing of mixed read/write requests based on the disk’s capabilities. This boosts throughput, reduces latency, and minimizes the impact of admin operations. It also reduces latency for real-time requests while running admin operations like scaling out.
Tap the full power of high-performance cloud computing instances such as the new EC2 I4i instances with ScyllaDB’s close to the hardware design. Benchmark results show 2X improvement in throughput compared to the i3 instances on the same number of vCPUs.
ScyllaDB’s new adaptive caching strategy removes the performance penalty traditionally associated with large partitions – even with reversed queries. ScyllaDB can now handle even a 100GB partition with ease.
Unbucketed time window compaction simplifies data modeling for time series data. Each time series can span as many time windows as it needs to; we’ll handle the logistics.
Get strong, immediately consistent schema updates, topology changes, tables and indexes, and more using the Raft consensus protocol. This eliminates schema and data conflicts, enables rapid and safe increases in cluster capacity, and provides a leap forward in manageability. Schema updates are in Open Source 5.0.
Repair-based node operations provide significant improvements for performance and data safety. If an operation fails (for example from a network hiccup), it will resume from the same point. Plus, there’s no need to run repair before or after node operations.
Eliminate the risk of unwanted data resurrection with ScyllaDB automatically tracking the completion of repair operations and purging outdated tombstones. This improves performance by allowing compaction to remove tombstones earlier and reducing read amplification.
ScyllaDB is written on Seastar, an asynchronous, non-blocking runtime that works extremely well for building highly-reliable low-latency distributed applications. It’s a perfect complement for applications written in Rust. We offer a fully asynchronous Rust driver that uses the Tokio runtime. This will be the core code unifying our drivers, with language bindings to C++, C, /C++ and Python.
You can now create user-defined functions by simply providing source code represented in WebAssembly Text Format. Leverage Wasm in Enterprise 2022.1.
Enhancements in ScyllaDB Operator further streamline deployment and management of ScyllaDB clusters via Kubernetes.
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