Engineering guides
How databases and search actually work, illustrated
Deep, diagram-led guides to the internals behind every data platform: the foundations our engineers use every day.
Guide
Concurrency Control in Distributed Systems
Two requests reach for the same row at the same instant. One of them has to wait, lose, or lie: the whole discipline of concurrency control is deciding…
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Guide
Database Indexes in Practice
How real database indexes work in MySQL InnoDB and PostgreSQL: clustered vs heap storage, UUID vs time-ordered primary keys, composite index column order, covering indexes and index-only scans, why the planner ignores an index, and what every index costs on writes, with an interview talk track.
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Guide
Database Reads and Writes for System Design
Why sequential appends beat random writes by 6,000x, and how that shapes the database write path and read path: write-ahead logs, B-Tree vs LSM tree, indexes, cache-aside vs write-through vs write-back, group commit, replication lag, range vs hash sharding, hot keys and CQRS, with the trade-offs to name in an HLD interview.
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Guide
How Search Engines Work
How a full-text search engine finds and ranks results: the inverted index, text analysis (tokenising, stemming, stop words), postings lists and boolean queries, TF-IDF and BM25 scoring, Lucene segments and merges, and near-real-time refresh, explained from the book-index analogy up to system design interview answers.
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From the Data Engineering Cookbook
By Andreas Kretz, republished under the Apache License 2.0.
Cookbook
Advanced Data Engineering Skills
Platform design questions, connect and buffer tools (REST APIs, Kafka, Pub/Sub), batch and stream processing, Hadoop and Spark, data stores and visualization: the advanced chapter of the Data Engineering Cookbook.
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Cookbook
Data Engineering Case Studies
How companies such as Airbnb, Netflix, Spotify, Uber and Twitter build their data platforms: a curated index of engineering write-ups and talks from the Data Engineering Cookbook.
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