Databases
How relational and specialized data stores work under the hood — storage engines, transactions, query execution, replication, and operating Postgres and Redis at scale.
Relational Foundations
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Relational Model & Relational Algebra
budding
deep of deep
top
The mathematical contract behind relational databases: relations as sets of typed tuples, integrity constraints as invariants, and a closed algebra that turns queries into expressions the optimizer can safely transform.
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Functional Dependencies & Normalization
budding
deep of deep
top
A derivation-first guide to functional and multivalued dependencies, attribute closure, candidate keys, minimal covers, 3NF/BCNF/4NF, and decompositions that are lossless and—when possible—dependency-preserving.
Storage Engines & Durability
- B-Tree vs LSM Storage Engines planned target deep top
- WAL & Crash Recovery planned target deep top
Transactions & Concurrency
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Transactions, ACID & Atomic Operations
budding
deep of deep
top
How PostgreSQL transaction boundaries, constraints, WAL, atomic DML, retries, idempotency, outbox delivery, and two-phase commit combine—and where ACID stops.
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MVCC & Isolation Levels
budding
deep of deep
top
PostgreSQL tuple-version visibility, statement and transaction snapshots, concurrency anomalies, Read Committed, Repeatable Read, Serializable Snapshot Isolation, and whole-transaction retries.
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Locking & Deadlocks
budding
deep of deep
top
PostgreSQL table, row, predicate, and advisory locks; precise SELECT FOR UPDATE semantics; NOWAIT and SKIP LOCKED; deadlock prevention, retries, timeouts, and production diagnosis.
- VACUUM, Bloat & Autovacuum planned target working mid
Query Performance
- Indexing Strategies planned target deep top
- Query Planning & EXPLAIN planned target working high
- Connection Pooling planned target working high
Replication & Scale
- Replication & Failover planned target deep high
- Table Partitioning planned target working mid
- Schema Migrations at Scale planned target working high
Beyond OLTP
- OLTP vs OLAP & Columnar Storage planned target overview mid
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Wide-Column Stores & Bigtable Architecture
budding
deep of deep
high
How Bigtable-style systems combine sparse sorted rows, column families, timestamped versions, range tablets, logs, memtables, SSTables, compaction, garbage collection, and replication—and why row-key design is the query plan.
- Redis Internals & Data Structures planned target deep high
- Time-Series Storage planned target overview low