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Data Systems at Scale

Course Contents

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One Size Fits None: The Database Landscape Relational Databases: The Default for a Reason Key-Value Stores Document Databases Wide-Column Databases Graph Databases Time-Series Databases Full-Text Search Databases Vector Databases OLTP vs OLAP SQL vs NoSQL: The Decision Rubric Data Modeling for Scale: Entities & Access Patterns NoSQL Modeling: Denormalization & Single-Table Design Checkpoint: The Database Landscape & Data Modeling

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Inside a Database: The Journey of a Write B-Trees & B+ Trees LSM Trees & SSTables WAL & Durability: Why Committed Data Survives Indexes Deep-Dive MVCC: Readers Don't Block Writers How a Query Executes Checkpoint: Database Internals

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Replication Topologies Sync vs Async Replication & Failover Quorums: N, R, W The Consistency Spectrum CAP, Properly PACELC: CAP's Grown-Up Sibling Read Repair & Hinted Handoff Version Conflicts Codelab: Postgres Replication + Failover Checkpoint: Replication & Consistency

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The Read-Scaling Playbook Read Replicas & Replication Lag Denormalization Materialized Views Connection Pooling for Databases Query Optimization in Practice Caches & Databases: Read-Your-Writes Coherence Checkpoint: Scaling Reads

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Partitioning vs Sharding Choosing a Shard Key Consistent Hashing Resharding & Hot Shards Federation Distributed ID Generation Write Batching & Buffering Codelab: Partition a Dataset Checkpoint: Scaling Writes & Partitioning

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ACID, Precisely Isolation Levels & Their Anomalies Pessimistic vs Optimistic Locking The Distributed Transaction Problem Two-Phase Commit (and Why 3PC Exists)Saga: The Data-Consistency Mechanics Outbox + CDC: Reliable Events from Your Database Idempotency as a Discipline Flash Sale: Inventory Under Contention Codelab: Trigger Isolation Anomalies Checkpoint: Transactions & Concurrency

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Block vs File vs Object Storage Design an S3: Blob Storage as a System Distributed File Systems Erasure Coding vs Replication Media Chunking Video Transcoding Pipelines Tiered & Cold Storage Checkpoint: Storage Systems

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When Ordinary Indexes Fail Geospatial Search: The Problem Geohash Quadtrees R-Trees S2 & H3 Bloom Filters Cuckoo Filters HyperLogLog Count-Min Sketch MinHash & Similarity Sketches Inverted Index + TF-IDF/BM25 Skip Lists & Merkle Trees Checkpoint: Specialized Indexes & Sketches Capstone Pass 2: The Marketplace Data Layer

Geospatial Search: The Problem

Define the geospatial search problem behind every map and ride app — what near means, three shapes of near, why the obvious answers die, and what a spatial index must do.

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