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Databases Articles

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

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Databases

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

Cache invalidation is hard because the cache is not the source of truth. It is a copy, and every copy has a consistency problem. The real question is not "how do we make cache perfectly consistent?" The better question i…

Apr 7, 2026·5 min read

#cache invalidation#redis#caching

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Databases

Cassandra Data Modeling: Design for Queries, Not Entities

Cassandra is a write-optimized distributed database built for linear horizontal scalability. It stores data in a distributed hash ring — every node is equal, there's no primary, and data placement is determined by partit…

Jun 18, 20259 min read

#cassandra#nosql#data modeling

Databases

DynamoDB Advanced Patterns: Single-Table Design and Beyond

DynamoDB is a fully managed key-value and document database that delivers single-digit millisecond performance at any scale. It achieves this with a fundamental constraint: you must define your access patterns before you…

Jun 13, 20259 min read

#dynamodb#aws#nosql

Databases

Zero-Downtime Database Migrations: Patterns for Production

Database migrations are the most dangerous part of a deployment. Application code changes are stateless and reversible — rollback a bad deploy and your code is back to the previous version. Database schema changes are st…

Jun 8, 20258 min read

#database#migrations#postgresql

Databases

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

PostgreSQL ships with defaults tuned for a 512MB machine from 2005. Every production deployment needs to be re-tuned. Beyond that, most slow queries are not a PostgreSQL problem — they're a query design problem that Post…

Jun 3, 20259 min read

#postgresql#databases#performance

Databases

Elasticsearch Query Optimization: From Slow to Sub-100ms

Elasticsearch is a distributed search and analytics engine built on top of Apache Lucene. At small scale, it's fast regardless of what you do. At production scale — billions of documents, hundreds of concurrent queries, …

May 29, 20258 min read

#elasticsearch#search#performance

Databases

Redis Caching Strategy at Scale: Beyond Simple Key-Value

Every senior engineer has fought a caching bug that looked simple and turned out to be a distributed systems problem. Cache stampedes, thundering herds, avalanche failures — these happen at scale and they are expensive. …

May 3, 202511 min read

#redis#caching#java

Databases

Designing a Database Sharding Strategy for 100 Million Users

Vertical scaling has a ceiling. For most applications, that ceiling arrives somewhere between 1 million and 10 million users, depending on write patterns and data size. At 100 million users, the question is not whether t…

Apr 14, 20259 min read

#databases#sharding#postgresql

Databases

Time-Series Databases: InfluxDB vs TimescaleDB vs Prometheus

Time-series data is fundamentally different from general-purpose data: it arrives in time order, is queried by time ranges, has predictable decay in value, and has write patterns that overwhelm traditional relational dat…

Mar 29, 202511 min read

#time-series#influxdb#timescaledb

Databases

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

Indexes are the single most impactful optimization in database performance. A 10-second query becomes 20ms with the right index. A wrong index slows writes and misleads the query planner. Understanding the internals — no…

Mar 9, 202512 min read

#postgresql#indexing#b-tree

Databases

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

Most engineers use Elasticsearch as a black box: index some JSON, run a search, get results. When search quality is poor or performance degrades at scale, they reach for random settings without understanding why. This ar…

Feb 24, 202511 min read

#elasticsearch#search#inverted index

Databases

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

Most teams use Redis for one thing: caching. They store objects with a TTL, check the cache before hitting the database, and call it a day. This barely scratches the surface. Redis is a data structure server. Its real po…

Jan 22, 202513 min read

#redis#cache#java

Databases

PostgreSQL vs MongoDB vs DynamoDB: When to Use Which Database

Every database choice is a bet on your access patterns. PostgreSQL, MongoDB, and DynamoDB are all excellent databases — for different problems. The mistake engineers make is choosing based on hype ("NoSQL scales better")…

Jan 12, 202511 min read

#postgresql#mongodb#dynamodb

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