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Database engineering guides for PostgreSQL, Redis, Elasticsearch, DynamoDB, indexing, caching, and production data access patterns.

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Databases

MySQL Mastery: Relational Fundamentals and Setup

Mental Model > A relational database is like a collection of highly organized, interlinked spreadsheets where data integrity and structure are mathematically guaranteed. In a world increasingly obsessed with NoSQL, MySQL…

May 5, 20264 min readBeginnerDeep Dive

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Complete MySQL Mastery Roadmap

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DatabasesIntermediate

MySQL Mastery: Joins and Aggregations

Mental Model > Joins are the bridges that connect isolated islands of data. Aggregations are the funnels that summarize those islands into actionable insights. A database with a single table is just a slow Excel spreadsh…

Databases Articles

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MySQL Mastery: Relational Fundamentals and Setup

More Databases Guides

MySQL Mastery: Joins and Aggregations

MySQL Mastery: Indexing and Performance

MySQL Mastery: Transactions and ACID Properties

MySQL Mastery: Window Functions and Advanced Analytics

MySQL Mastery: Advanced Query Optimization

MySQL Mastery: InnoDB Architecture and Storage Engines

MySQL Mastery: Replication and High Availability

MySQL Mastery: Sharding and Horizontal Scaling

MySQL Mastery: Security and Operations

Bloom Filters: The Speed Secret of Modern NoSQL Databases

Cassandra Gotchas: Dealing with Tombstones and Wide Partitions

Cassandra Internals: LSM-Trees, Gossip, and Eventual Consistency

Cassandra Multi-Region Architecture: Designing for Global Scale

The CDC Playbook: Real-time Syncing between PostgreSQL and Elasticsearch

Optimistic vs. Pessimistic Locking: Concurrency Control in Practice

Database Sharding Part 1: The Vertical Ceiling

Database Scaling Part 2: Partitioning vs. Sharding

Database Sharding Part 3: The Shard Key Blueprint

Database Sharding Part 4: Consistent Hashing Internals

Database Sharding Part 5: The Scatter-Gather Problem

Database Sharding Part 6: Zero-Downtime Re-sharding

Distributed Caching at Scale: Mitigating the Thundering Herd

Distributed Transactions Part 6: Event Sourcing & CQRS

DynamoDB Pitfalls: Throttling, Hot Partitions, and the 400KB Limit

DynamoDB Single Table Design: Advanced Modeling Patterns

The Expand-Contract Pattern: Zero-Downtime Database Schema Changes

Query Optimization: The Hidden Cost of Cross-Shard Joins

Database Statistics: How Query Planners Build Histograms

Hybrid Logical Clocks (HLC): Solving Distributed Time & Causality

Inside the Linux Page Cache: The Invisible Database Accelerator

LSM-Tree Compaction Strategies: Leveled vs. Size-Tiered

MongoDB Aggregation Pipeline: Optimization and Performance

MongoDB Anti-Patterns: From Unbounded Arrays to Shard Imbalance

MongoDB Internals: Deep Dive into WiredTiger and Replication

Negative Result Caching: Protecting Databases

NoSQL Schema Evolution: Strategies for Zero-Downtime Data Growth

PostgreSQL JIT Tuning: Understanding the Cost

PostgreSQL MVCC: How Transactions Work Without Locking

PostgreSQL Vacuum Tuning: Internals of Bloat Control

Redis in Production: 5 Common Pitfalls and How to Avoid Them

Redis Internals: Event Loop, Data Structures, and Persistence

Redis Lua Scripting: Ensuring Atomicity in Complex Workflows

The Shadow Database Pattern: Verifying Schema Changes with Production Traffic

B-Trees vs. LSM-Trees: The Battle of Storage Engine Internals

SQL vs NoSQL: Which One for Your Next Production MVP?

Vector Search in NoSQL: Redis and MongoDB as Vector Databases

The Write-Ahead Log (WAL): The Universal Engine of Data Durability

Zero-Downtime Migration: Moving from SQL to NoSQL

PostgreSQL Locking Playbook: Deadlocks, Blocking Queries, and Timeouts

Cache Invalidation Patterns: TTL, Write-Through, Cache-Aside, and Event-Driven Eviction

Cassandra Data Modeling: Design for Queries, Not Entities

DynamoDB Advanced Patterns: Single-Table Design and Beyond

Zero-Downtime Database Migrations: Patterns for Production

PostgreSQL Performance Tuning: From Slow Queries to Sub-Millisecond Reads

Elasticsearch Query Optimization: From Slow to Sub-100ms

Redis Caching Strategy at Scale: Beyond Simple Key-Value

Designing a Database Sharding Strategy for 100 Million Users

Time-Series Databases: InfluxDB vs TimescaleDB vs Prometheus

Database Indexing Deep Dive: B-Trees, Hash Indexes, and Query Planning

Elasticsearch Deep Dive: Inverted Index, Mappings, and Query DSL

Redis Beyond Cache: Sorted Sets, Streams, and Pub/Sub Patterns

PostgreSQL vs MongoDB vs DynamoDB: When to Use Which Database

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