Database Insights

Walk through PostgreSQL's multi-process architecture, shared/local memory layout, page-organized storage, MVCC tuple versioning, the WAL write path, the query execution pipeline, and physical + logical replication — all with ASCII flow diagrams that show how data and control actually move through the system.

Deep dive into InnoDB storage engine internals. Understand buffer pool, redo log, undo log, change buffer, and adaptive hash index for expert-level MySQL optimization.

Twelve schema design patterns that survive production scale: primary key strategy, normalization trade-offs, partitioning, sharding boundaries, and indexing rules.

MySQL architecture from query parser to disk: optimizer pipeline, InnoDB buffer pool, redo log, and storage internals every production DBA needs in 2026.

Eliminate stale cache reads and thundering-herd stampedes by streaming MySQL binlog changes to Valkey via Debezium CDC. Full Java setup with embedded engine and XFetch.

Design multi-tenant databases — compare schema-per-tenant, row-level-security, and database-per-tenant approaches

Build a real-time analytics pipeline from PostgreSQL to ClickHouse using CDC — architecture, latency, and schema mapping

Understand the differences between OLAP and OLTP systems — query patterns, storage engines, and when to use a hybrid approach

Use Apache Airflow to orchestrate database ETL, backup jobs, and maintenance tasks — DAGs, sensors, and best practices

Implement the transactional outbox pattern to publish events reliably from MySQL or PostgreSQL without dual-write problems

Compare Delta Lake, Apache Iceberg, and Apache Hudi — ACID transactions, time travel, and format interoperability

Compare CDC, ETL, and ELT — latency, complexity, cost, and when each pattern fits your data pipeline needs