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.

Cut AWS database costs systematically: find over-provisioned RDS with Compute Optimizer, stop dev DBs after hours, buy Reserved Instances, and control storage growth.

Four configuration mistakes account for 60% of AWS database waste. Learn to right-size to Graviton3, convert gp2 to gp3 storage, audit idle replicas, and use Reserved Instances to cut your database bill by 25-40%.

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.

Configure Aurora Serverless v2 for production workloads. ACU sizing, RDS Proxy integration, CloudWatch monitoring, and cost vs provisioned comparison.

Cut Amazon RDS costs with right-sizing, Reserved Instances, Aurora Serverless v2, and snapshot lifecycle management. Practical techniques with real savings estimates.

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.