Inside Xinghuan Tech’s Next‑Gen Big Data 3.0 Architecture: Unified, Cloud‑Native, Real‑Time

This article details Xinghuan Technology’s evolution from 2013 to the present, describing its self‑developed Big Data 3.0 stack—including a unified data platform, SQL‑centric development, cloud‑native resource scheduling, distributed storage managed by Raft, DAG‑based compute engines, and real‑time stream processing—while highlighting key milestones and design principles that differentiate it from traditional Hadoop‑based solutions.

Data PlatformReal-time ProcessingSQL Optimizer

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Inside Xinghuan Tech’s Next‑Gen Big Data 3.0 Architecture: Unified, Cloud‑Native, Real‑Time

Alibaba Cloud Developer

Sep 10, 2021 · Databases

Inside MySQL 8.0 Optimizer: From SQL String to Execution Plan

This article walks through MySQL 8.0’s SQL optimizer, explaining how a raw SQL statement is parsed, transformed, and optimized through stages such as Setup, Resolve, Derived‑table merging, materialization, window‑function handling, and ROLLUP processing, illustrated with diagrams and code examples.

Query ExecutionRollupSQL Optimizer

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Inside MySQL 8.0 Optimizer: From SQL String to Execution Plan

Baidu Geek Talk

Aug 4, 2021 · Databases

How Baidu’s BaikalDB Redefined Distributed Storage for Massive Ad Platforms

This article analyzes the evolution of Baidu's advertising data storage, detailing the business-driven requirements, the design and development of the BaikalDB distributed database, its architecture across storage, compute and scheduling layers, key features such as Raft replication and multi‑index support, and the lessons learned for building cloud‑native, high‑performance databases.

BaikalDBCloud NativeRaft replication

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How Baidu’s BaikalDB Redefined Distributed Storage for Massive Ad Platforms

DataFunTalk

Apr 22, 2019 · Databases

Deep Dive into TiDB SQL Optimizer and Execution Engine

This article provides a comprehensive technical overview of TiDB's architecture, its SQL optimizer—including logical and physical optimization phases, rule‑based transformations, join ordering, and statistics collection—and outlines future work to improve query planning stability and performance.

Database InternalsQuery PlanningSQL Optimizer

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Deep Dive into TiDB SQL Optimizer and Execution Engine