Databases
Stored Procedures: When to Use Them, When to Avoid Them
Opinionated guide to stored procedures covering performance benefits, maintainability costs, security implications, and practical guidelines for when they help vs hurt.
Databases
Databases
Snapshots vs Volumes: Understanding Cloud Storage Primitives
Practical guide to cloud storage snapshots and volumes covering architecture, performance, cost optimization, backup strategies, and disaster recovery patterns.
Databases
Columnar vs Row Databases: Architecture, Performance, and Use Cases
In-depth comparison of columnar and row-oriented databases covering storage architecture, compression, query performance, and choosing the right one for your workload.
Databases
Database Normalization and Denormalization: When to Use Each and Why
Practical guide to database normalization and denormalization with real-world examples, covering normal forms, performance tradeoffs, and when to break the rules.
Databases
Database Replication: Streaming vs Logical Replication Explained
Deep dive into streaming and logical database replication, covering architecture, performance tradeoffs, failover strategies, and when to use each approach.
Databases
SSD vs HDD: How to Choose the Right Storage for Your Workload
Practical guide to choosing SSD or HDD storage for databases, analytics, and archival workloads based on real-world performance, cost, and endurance tradeoffs.
Databases
Sharding vs Partitioning: Database Scaling Strategies Compared
Sharding and partitioning are related but different database scaling strategies. A veteran architect explains both approaches, their trade-offs, and when to use each.
Databases
The CAP Theorem Explained: Consistency, Availability, and Partition Tolerance
The CAP theorem is widely cited and widely misunderstood. A veteran architect explains what it actually means, why it matters, and how real databases navigate it.
Databases
ACID Properties in Databases: Atomicity, Consistency, Isolation, Durability Explained
ACID properties are the backbone of reliable databases. A veteran architect explains atomicity, consistency, isolation, and durability with real-world examples.
Databases
Distributed Caching Explained: Redis, Memcached, Valkey, and How to Choose
A principal architect's guide to distributed caching: how Redis, Memcached, and Valkey work, when to use each, and lessons from running caches at scale in production.
Databases
SQL vs NoSQL Databases: Architecture, Trade-offs, and Choosing the Right One
SQL and NoSQL databases are not interchangeable. A principal architect with 30 years of database experience explains the real differences and when to use each.
Databases
Vector Databases Explained: pgvector, Pinecone, Weaviate and How to Choose
A practical guide to vector databases for AI applications: when to use pgvector vs dedicated vector DBs, how ANN indexing works, and what I've learned shipping RAG systems in production.
Databases
RAID Levels Explained: RAID 0, 1, 5, 6, 10 and How They Actually Work
A practical guide to RAID 0, 1, 5, 6, and 10 from someone who has rebuilt arrays at 3 AM. Learn how each RAID level works, performs, and fails.
Databases
Block vs Object vs File Storage: Use Cases, Trade-offs, and When to Use Each
Block, object, and file storage serve fundamentally different purposes. A veteran architect explains how each works, their trade-offs, and when to choose which.
Databases
SAN vs NAS vs DAS: Understanding Storage Architecture Differences
Learn the real differences between SAN, NAS, and DAS storage architectures. A veteran architect breaks down performance, cost, and use cases for each approach.