SurrealDB 3.0 benchmarks: a new foundation for performance

SurrealDB 3.0 introduces significant performance improvements over its predecessor, SurrealDB 2.0, by restructuring its execution engine and enhancing its benchmarking capabilities. The new version of this multi-model database, which integrates relational, document, graph, time-series, key-value, vector, geospatial, and full-text workloads, has been optimized to address high-throughput, business-critical workloads. Key enhancements include a more efficient query execution model that transitions from AST to LogicalPlan to ExecutionPlan, resulting in substantial speed increases for operations like graph queries, large table scans, and vector searches. The introduction of an open-source benchmarking tool, crud-bench, facilitates thorough testing across various workloads, ensuring transparent and balanced performance evaluations. SurrealDB 3.0's architectural updates have led to dramatic improvements in concurrency and throughput, making it a robust option for enterprises like Tencent that require scalable and reliable database solutions. Additionally, future updates promise to expand and optimize the database's capabilities further, focusing on streaming execution and indexing improvements.