《Designing Data-Intensive Application》DDIA 第一版 / 第二版 中文翻译
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Updated
Sep 22, 2026 - Python
《Designing Data-Intensive Application》DDIA 第一版 / 第二版 中文翻译
A collection of Claude Code skills that enforce coding discipline and prevent common AI coding anti-patterns.
读书笔记
Design Data Intensive App Notes
Build AI coding principles for Claude Code, with discipline rules and system design guides to improve code quality and reduce bad patterns
A Claude Code skill that runs an end-to-end system design course — anchored to DDIA and the System Design Primer, with real-world incidents, runnable exercises, and mock interviews.
I asked AI to write tech comics
100 days of progress in DDIA. From architecture fundamentals, storage, replication, sharding, transactions, distributed failures, consistency/consensus and batch/stream processing to architecture capstone.
An Agent Skill for applying DDIA principles to real engineering decisions
📚 Agent skills distilled from technical books — AI Engineering, Context Engineering, Designing Data-Intensive Applications, and more. Agent-agnostic, plain Markdown. Give your AI agent a bookshelf.
Interactive distributed-systems visualizations + hand-built mini systems (LSM engine, Raft, Gossip Glomers) — a DDIA 2nd-ed learning project
Interactive study platform for Designing Data-Intensive Applications. Chapter quizzes, spaced repetition flashcards, timed exams, and AI-powered grading with personalized feedback.
A first-principles engineering notebook rebuilding Designing Data-Intensive Applications, chapter by chapter, with working TypeScript implementations for every core mechanism (storage engines, replication, consensus, stream processing, and more).
An educational distributed database engine built in Go. Brings the concepts of "Designing Data-Intensive Applications" (DDIA) to life with LSM-Trees, 2PC, Raft consensus, and Vector Clocks.
Implementation of "Designing Data Intensive Application" Book
Boutquin.Storage is a collection of data storage algorithms implemented in C# using a clean architecture approach. This repository is designed to provide efficient and scalable solutions for data-intensive applications.
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