The JusDB Database Engineering Blog

Implement database CI/CD with Flyway migrations, GitHub Actions pipelines, pytest schema tests, and blue-green deployment patterns. Eliminate ad-hoc schema changes.

Execute MySQL schema migrations safely with the expand-contract pattern, batched backfills, backward-compatible changes, and migration tooling comparison (Flyway, Liquibase, gh-ost).

Monitor ETL pipelines with data freshness checks, row count reconciliation, dbt data quality tests, and Slack alerting. Detect silent failures before users do.

Deploy Kafka Connect with JDBC source connectors, Single Message Transforms, Dead Letter Queues for error handling, and consumer group lag monitoring.

Set up Debezium to stream MySQL and PostgreSQL changes to Kafka. Covers prerequisites, connector deployment, change event structure, and replication slot monitoring.

Use Apache Flink CDC to capture MySQL and PostgreSQL changes — stateful processing, exactly-once semantics, and Kubernetes deployment

pgvector brings vector similarity search to PostgreSQL — enabling semantic search, recommendation engines, and RAG pipelines without a separate vector database.

Apply GitOps principles to database changes — PR-based schema reviews, automated migrations, and rollback strategies

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

Compare streaming and batch data processing — latency, throughput, tooling, and when each approach makes sense