An alternative to sharding a MongoDB replica set that outgrew its memory: a proof of concept A replica set that no longer fits in memory Most MongoDB replica sets start small. The working set fits in ...

Thread Pool in Percona Server and MySQL (Part 2) The previous Part 1 focused on explaining the idea of thread pool, configuration options and analysis of thread pool efficiency in Percona Server for M...

Thread Pool in Percona Server and MySQL (Part 1) A new version of Community MySQL Server July release contains two versions 26.7.0 and 9.7.2. It is an important milestone because it finally brings a T...

Percona ClusterSync for MongoDB (PCSM) synchronizes data from a source MongoDB cluster (including Atlas) to a target MongoDB cluster in two stages. It first creates a consistent starting point and clo...

Percona Toolkit’s pt-online-schema-change (pt-osc) has long been the preferred solution for performing online schema changes with minimal downtime. Its chunk-based copy algorithm is designed to adapt ...

Reducing operational blast radius in distributed systems is a constant challenge. Learn how our new subclustered placement algorithm for M3DB limits shard migration impact, enables safer parallel operations, and improves predictability as our clusters scale. #DistributedSystems #DatabasePerformance #UberEngineering

Slow SQL queries degrade user experience, cause cascading failures, and turn simple operations into production incidents. The traditional fix? Collect more telemetry. But more telemetry means more…

The article discusses the performance of Pgrust, a database system leveraging LLM-driven optimization, on the ClickBench benchmark. While Pgrust shows strong results in specific queries, concerns arise about overfitting to benchmarks rather than general design improvements. The cost model and profile-guided optimization (PGO) corpus for ClickBench include queries with similar structures, suggesting potential overfitting. The text also highlights that JIT compilation is not uncommon in databases, citing examples like Umbra, CedarDB, SingleStore, Amazon Redshift, and Apache Impala. Additionally, FRE, an LLM-generated regex engine, is noted for its performance on specific benchmarks but lacks broad generalization. SLOC estimates reveal FRE's codebase is significantly larger than rust-lang/regex, raising questions about trade-offs between compilation time and runtime efficiency. The piece also touches on broader trends of software performance degradation, contrasting real-world issues with psychological illusions of decline. Overall, the article balances technical analysis with critiques of benchmarking practices and optimization strategies in modern software development.

LeadByte migrated from AWS to Percona, gaining a more cost-effective, high-performance database environment without sacrificing reliability or scalability.

Your database moves much too slowly while API requests persist for endless durations. You’re not alone! The database performance of many…

Unlock the secrets of SQL Server's Batch Requests/Sec metric. This guide explains what it is, why it matters, and how to optimize your database performance.

Postgres in Rust: Boost database performance and security with a rewritten core