The JusDB Database Engineering Blog

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.

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

RDS MySQL audit logs stored in CloudWatch cost significantly more than S3 — and most teams don't need real-time log access. Here's how to export audit logs to S3 and cut your AWS bill.

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.

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 measurement-led guide to RDS and Aurora cost control: right-size safely, cover steady usage, govern storage, schedule idle systems, and verify each change.

DynamoDB and MongoDB are the two most common NoSQL choices, but cost structures, query flexibility, and operational overhead differ dramatically depending on your access patterns.

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.

Aurora PostgreSQL offers sub-30-second failover and 15 read replicas but costs more per instance and adds per-I/O pricing. Learn when Aurora's HA wins over RDS simplicity with real cost modeling for 2025.

AWS RDS, Aurora, and Aurora Serverless v2 all run MySQL and PostgreSQL — but their pricing models differ dramatically. Learn when to use each and how to avoid expensive I/O surprises.

Migrate from DynamoDB to Aerospike for better cost-performance at scale. Real case study showing 60% cost reduction with improved latency and throughput.