The Aikesheng Open Source Community provides stable, enterprise‑grade MySQL open‑source tools and services, releases a premium open‑source component each year (1024), and continuously operates and maintains them.
This article presents a comprehensive benchmark of 19 large language models (plus a human baseline) on generating analytical SQL queries over a 200 million‑row GitHub events dataset, detailing the methodology, metrics, results, and practical guidance for using LLMs in data analysis.
The article examines the shortcomings of conventional AI evaluation methods, introduces the concept of an "unknown" risk in production settings, and presents SCALE—a continuously updated, high‑fidelity benchmark that stresses large‑model SQL capabilities with real‑world incident data and mixed objective‑subjective scoring.
The article argues that conventional AI evaluation metrics miss critical unknown risks, outlines three key challenges in AI model selection for database tasks, introduces the SCALE benchmark with real‑world incident data, and explains its mixed evaluation framework that combines objective, subjective, and performance‑driven assessments to guide tech leaders toward reliable SQL‑focused AI solutions.
This guide presents practical, DBA‑tested MySQL replication best practices—including GTID, row‑based replication, mandatory primary keys, schema consistency, binlog tuning, read‑only protection, dedicated replication users, latency monitoring, parallel workers, and SSL encryption—to ensure reliable, predictable replica behavior.
This article explains the most impactful MySQL InnoDB variables, shows how to monitor their key metrics, provides concrete adjustment guidelines, and highlights when each tweak improves performance or can unintentionally degrade it.
The January 2026 SCALE benchmark adds an index‑suggestion metric and evaluates two new LLMs—智谱 GLM‑4.7 and 字节跳动 Seed‑OSS‑36B—revealing strengths in dialect conversion, moderate SQL understanding, and notable gaps in complex execution‑plan analysis and practical index recommendations.
This guide explains how to use MyDumper for logical backups and MyLoader for fast, parallel replica reconstruction, covering backup parameters, metadata configuration, replication setup, handling faulty replicas, and final restoration steps to ensure data consistency and minimal downtime.
MySQL 9.6 shifts foreign‑key checks and cascade handling from the InnoDB storage engine to the SQL engine, eliminating hidden changes, improving binary‑log visibility, and delivering full‑log replication and analytics without sacrificing performance.
This article explains MySQL’s Optimizer Trace feature, covering its purpose, required system variables, how to enable it, the structure of its JSON output, and how to interpret the preparation, optimization, and execution stages to diagnose query‑plan decisions.
MySQL’s ORDER BY DESC queries run slower than ASC because InnoDB stores records in a forward‑oriented singly linked list, using an infimum‑supremum structure, a page directory, and N_OWNED fields, which make backward scans O(n) while forward scans remain O(1).
