Susan Pierce

The database is the last bottleneck in your dev workflow Database branching is the missing primitive in modern development workflows. Every other part of the stack has evolved to support fast iteration. Code has Git. Infrastructure has Terraform. Deploys have CI/CD pipelines that run in minutes. But relational databases still work the way they did ten years ago. Most teams share a single staging database. Within days of being set up, that database drifts out of sync with production.

You only have 2 choices when provisioning databases: Over-provision: set your compute high for the worst case scenario and over-pay for idle CPU Under-provision: save cash now by setting compute low but a workload spike will cripple your system later This is the “provisioning paradox”, and if you’ve ever managed a production database, you’ve faced this challenge. For years, we’ve just accepted this as the cost of doing business with relational databases.

For years, a data wall has separated the world of application development from the world of analytics. Developers have been forced to bridge this gap with brittle ETL pipelines just to move data from an operational PostgreSQL instance to a data lake. This fragmentation does more than just slow down delivery; it creates a data tax of duplicated storage and a persistent lag between reality and insight.