Databases
PostgreSQL EXPLAIN ANALYZE: Reading Query Plans Like a Senior DBA
Stop guessing why your queries are slow. Learn to read PostgreSQL query plans at a level where you can actually fix problems - seq scans, join strategies, row estimate disasters, and the N+1 you didn't know was hiding in your ORM output.
Drizzle ORM vs Prisma in 2026: A Production Engineer's Honest Comparison
Both ORMs are genuinely good. The choice depends on your migration discipline, whether you hit Prisma's edge runtime limitations, and how much you care about the SQL Drizzle generates vs the DX Prisma provides. Here's the honest comparison - same query, both ORMs, real trade-offs.
Postgres BML: Binary Model Loading and Vector Speed (2025)
Postgres is no longer just for rows. In 2025, BML allows us to load ML models directly into the database for ultra-low latency inference.
How to Scale MySQL with Read Replicas When Your App Slows Down (2015)
When a single MySQL server handles both reads and writes, reads win and writes stall. Adding a read replica splits the load: writes go to master, reads go to replica. This is the exact setup - my.cnf, replication config, PHP connection routing - we used when our app hit 50k daily users.
InfluxDB: TSM Engine and the Cardinality Trap (2014)
Moving from LevelDB to TSM was a bold move. Let's see how InfluxDB handles millions of series and why high cardinality is your worst enemy.
The Big Data Hype (2012): How Hadoop and MongoDB Started the Data Revolution
In 2012 'Big Data' was on every slide deck. MongoDB was going to replace MySQL. Hadoop was going to process everything. We lived through the hype and learned what was real.
Apache Storm: Spouts, Bolts, and Topologies (2012)
Hadoop is for batches. Storm is for streams. Let's build a real-time word count that doesn't melt your cluster.
MySQL Optimization: How We Handled 100,000 Daily Queries on PHP 5.3
Case study of migrating from MyISAM to InnoDB and introducing Memcached for heavy SQL query caching in a high-load portal. Before/after performance benchmarks.
MongoDB 1.6: Scaling Out with Sharding and Replica Sets (2010)
The NoSQL revolution is in full swing. With MongoDB 1.6, horizontal scaling and automated failover are finally production-ready. Let's configure a sharded cluster.
Redis: RDB vs. AOF Persistence (2009)
Redis is fast because it's in-memory, but what happens when the power goes out? Choosing between RDB and AOF is a classic trade-off.
CouchDB: Scaling with MapReduce and Incremental Views (2009)
2009 is the year of the 'NoSQL' movement. CouchDB is leading the charge with its document-based storage and powerful MapReduce indexing system.
MongoDB: When Your Data Doesn't Fit in a Table
The 10gen team has released MongoDB. It's 'humongous' (supposedly), it's NoSQL, and it uses JSON. Is the relational era over?