Expert insights on database management, performance optimization, and reliability engineering from industry professionals
Showing 12 of 387 articles
A practical guide to choosing between read replicas and caching layers — replication lag behavior, cache invalidation strategies, thundering herd prevention, tiered read architecture patterns, and decision framework.
Hatchet transforms raw MongoDB JSON logs into actionable insights — surfacing slow operations, connection storms, and namespace hotspots that are impossible to spot in raw log files.
Transform PostgreSQL into a vector database with pgvector. Learn embedding storage, ANN index creation, similarity search optimization, and AI/ML integration patterns.
Apply GitOps principles to database changes — PR-based schema reviews, automated migrations, and rollback strategies
How to size your database connection pool correctly — the HikariCP formula, the variables that determine optimal pool size, and the mistakes that cause connection exhaustion or underutilization.
MySQL 8.0 introduced EXPLAIN FORMAT=TREE — a hierarchical, human-readable query plan format that reveals join order, access methods, and cost estimates in a way that the traditional tabular EXPLAIN cannot.
Accelerate analytics with StarRocks MPP database. Learn vectorized execution, CBO optimizer, materialized views, and real-time data ingestion for sub-second query performance.
Compare CockroachDB, Google Spanner, and YugabyteDB — consistency models, PostgreSQL compatibility, and operational costs
MySQL 8.0 introduced multi-valued indexes — allowing you to index individual elements of a JSON array so queries using MEMBER OF or JSON_OVERLAPS can use an index.
A production guide to zero-downtime database migrations — why ALTER TABLE causes downtime, the Expand-Contract pattern, safe migration patterns for PostgreSQL and MySQL, and tooling with Flyway, Liquibase, pt-osc, and gh-ost.
UUIDs as primary keys can destroy database performance. Learn why 50M rows went from 0.5ms to 2.3ms inserts, and how to fix it with hybrid approaches.
Add data quality checks to your pipeline — row count validation, schema drift detection, and anomaly alerting with Great Expectations
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