SurrealDB announced the release of performance benchmarks for SurrealDB 3.0, highlighting foundational architectural improvements that deliver more stable and predictable performance across multi-model workloads. The benchmarks reflect SurrealDB’s commitment to providing developers and enterprises with a unified database platform capable of handling relational, document, graph, time-series, key-value, vector, geospatial, and full-text use cases within a single engine.
As part of its ongoing engineering journey, SurrealDB has expanded its internal benchmarking methodology to measure the impact of fundamental changes introduced in version 3.0. This new benchmark suite focuses on real-world performance characteristics under diverse workloads and evaluates how internal rearchitecting efforts have translated into tangible results for users.
SurrealDB’s internal benchmarking tool, crud-bench, was developed in Rust to consistently test and monitor performance across embedded, networked, and remote deployment modes. Unlike many generic benchmarking suites, crud-bench is designed to evaluate the broad feature set unique to SurrealDB, from SQL-style queries to multi-model data access patterns, enabling continuous measurement of performance impact for internal engine changes.
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The 3.0 benchmark results demonstrate the effects of substantial architectural improvements at the core of SurrealDB. Key enhancements include a redesigned query execution engine that transitions SurrealQL through a more standardized optimization pipeline and streamlines query execution for greater throughput and consistency. These architectural shifts provide a stronger foundation for performance and lay the groundwork for future optimizations.
SurrealDB emphasized that its multi-model design presents unique benchmarking challenges compared with single-purpose databases, as each class of workload — from vector search to graph traversal — demands tailored evaluation. The company continues to refine its methodology to ensure transparent, balanced comparisons while inviting community feedback on benchmark improvements.
Looking ahead, SurrealDB plans to extend its benchmarking efforts to include broader comparisons against other database platforms across varied workload types, enabling customers and developers to better understand the performance profiles of different systems under real-world application scenarios.
SOURCE: SurrealDB