Database Internals: A Deep Dive into How Distributed Data Systems Work | Data Engineering & Databases | Oh My Learning

01 Hardware and IO Foundations for Storage Engines 10 min read mid drafted 02 Data Layout and File Organization on Disk 10 min read senior drafted 03 B-Tree Fundamentals and Page-Oriented Indexing 10 min read senior drafted 04 Write-Ahead Logging and Crash Recovery Basics 11 min read senior drafted 05 Buffer Management, Caching, and Compaction Pressure 11 min read senior drafted 06 LSM-Tree Design and the Read-Write Amplification Trade-off 10 min read senior drafted 07 SSTables, Compaction Strategies, and Tombstones 12 min read senior drafted 08 B-Tree vs LSM-Tree: Workload-Driven Engine Selection 9 min read senior drafted 09 In-Memory Structures and Lock-Free Indexing Patterns 10 min read senior drafted 10 Transaction Internals: MVCC, Snapshots, and Isolation Mechanics 10 min read senior drafted 11 Engine Architecture: Separating Storage, Execution, and Control Planes 10 min read staff drafted 12 Replication Logs, Shipping Models, and Durability Semantics 10 min read senior drafted 13 Quorums, Anti-Entropy, and Conflict Resolution in Replicated Stores 12 min read staff drafted 14 Partitioning Internals and Rebalancing Algorithms 11 min read staff drafted 15 Consensus Internals with Raft and Log Agreement Mechanics 10 min read staff drafted 16 Building and Evolving a Distributed Storage Engine in Production 11 min read staff drafted