Benchmarking Petabyte-Scale NoSQL Workloads with ScyllaDB

With the increasing demand for real-time applications handling petabyte-scale data, the importance of evaluating database performance at such scales has grown significantly. ScyllaDB conducted a foundational benchmark of its high-performance, low-latency database to assess its capability to manage extensive workloads effectively. The benchmark revealed that ScyllaDB could store a 1 PB dataset using only 20 large machines, achieving 7.5 million operations per second with single-digit millisecond latency, which underscores its storage density and cost efficiency. A key feature highlighted was workload prioritization, which allows users to allocate hardware resources based on task importance, enabling efficient cluster consolidation and reduced latency for smaller, critical workloads. The benchmark results serve as a valuable reference for understanding ScyllaDB's performance improvements and offer insights into conducting similar large-scale benchmarks.