Database Insights

Go beyond basics with Debezium — handle schema evolution, manage connector offsets, and build resilient CDC pipelines

Debezium reads MySQL binary logs and PostgreSQL WAL to stream every row-level change as a Kafka event in near real-time — replacing nightly batch ETL with sub-second data propagation.

Stream PostgreSQL changes to Kafka using pgoutput and Debezium — setup, monitoring, and lag management

Implement schema change management with versioning, peer review, and automated validation for safe deployments

Use PostgreSQL FDW to query MySQL, S3, MongoDB, and other databases from within PostgreSQL — setup and performance tips

Use Spark with JDBC to read from and write to relational databases — partition strategies, predicate pushdown, and write modes

Replicate OLTP databases to analytical warehouses — CDC, bulk load, incremental sync, and schema evolution handling

A production guide to TimescaleDB — hypertable setup, automatic chunk management, columnar compression policies, retention policies, continuous aggregates with time_bucket(), and comparison against InfluxDB and Prometheus.

Build a MySQL CDC pipeline using binlog and Kafka — Debezium, Maxwell, or Canal — trade-offs and production setup

Understand Kafka from a database perspective — partitions, offsets, consumer groups, and durability guarantees

Deep dive into advanced database indexing strategies including composite indexes, covering indexes, and partial indexes. Optimize query performance with expert indexing techniques.

Manage SQL schema migrations with Flyway — versioned and repeatable scripts, CI/CD integration, and team workflows