The JusDB Database Engineering Blog

A step-by-step guide to migrating an on-premises Microsoft SQL Server database to Amazon RDS for SQL Server — covering native backup/restore via S3 with the rds_restore_database stored procedure, AWS DMS full-load + CDC for near-zero downtime, option group and IAM setup, cutover, and post-migration hardening.

The decision matrix for the three Azure SQL flavors: eight constraints (cross-DB queries, SQL Agent, CLR, linked servers, networking, licensing…) that pick Managed Instance vs Azure SQL Database vs SQL Server on Azure VM, with a cost comparison and migration paths.

Choose the optimal EC2 instance for your database workload. Compare R, X, I, and Graviton families with real-world benchmarks and cost-performance analysis.

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

Use Aurora Serverless v2 for cost-effective scaling — ACU configuration, scaling behavior, and when it fits

2025 was the year databases competed on operational simplicity. Serverless databases matured, pgvector merged vector search into PostgreSQL, and CDC became standard infrastructure. Here's what mattered and what's next.

MongoDB Atlas M30 costs 5.6x more than equivalent EC2 instances, but self-hosted TCO includes DBA labor that most comparisons ignore. Here's the honest math and when each option wins.

Supabase, PlanetScale, and Neon each take a different approach to serverless databases. Compare their connection limits, branching features, cost models, and which fits your workload.

ClickHouse Cloud is convenient but can cost 3-5x more than a well-tuned self-hosted cluster at scale. This breakdown shows exactly where the cost lines cross.

Aurora and RDS share the MySQL engine but diverge at the storage layer in ways that produce very different cost and performance profiles — the right choice depends entirely on your I/O pattern.

A detailed comparison of ClickHouse and BigQuery for analytical workloads — MergeTree engine vs Capacitor storage, self-hosted vs serverless cost models, query latency, real-time ingestion, and when to choose each.

A detailed comparison of Google Cloud SQL, Amazon RDS, and Azure Database for MySQL and PostgreSQL — HA architecture, failover times, connection pooling, pricing for equivalent instances, and platform-specific features.