Why serverless Postgres is redefining data platforms

Pixetric started as an internal experiment: could we treat Postgres the way Git treats source code? Fast-forward to today and thousands of branches are created on the platform every week. This post breaks down the ideas behind Pixetric’s serverless Postgres fabric and why it matters for modern data products.

Compute and storage have different jobs

Traditional Postgres couples compute and storage. Scaling means provisioning larger instances, cloning disks, and scheduling maintenance windows. Pixetric separates the two:

• Durable storage fabric replicates data across zones and exposes copy-on-write blocks so branches spin up instantly.
• Elastic compute pools attach to any branch, boot in under a second, autoscale per workload, and suspend when idle to save money.

This architecture keeps the familiar Postgres surface area while unlocking the ergonomics of a serverless runtime.

Branching is more than convenience

We treat branches as first-class primitives. Engineers can:

• Create dev/staging/preview branches seeded with production snapshots.
• Run migrations and replay WAL changes before touching main.
• Promote or discard branches with optimistic locking so conflicts surface early.

Branching eliminates the “shared staging database” bottleneck and shortens review cycles.

Observability must be built in

When compute pools are ephemeral, you cannot rely on host-level dashboards. Pixetric ships query-level metrics, slow query capture, WAL throughput, and alerting out of the box. Teams get actionable insight without standing up Grafana stacks or scraping logs.

Security cannot be an afterthought

Every branch inherits organization-wide guardrails: TLS everywhere, audit logs, SSO/MFA, and policy-driven access control. Dedicated control planes add private networking and custom SLAs for regulated customers.

What’s next

We are investing heavily in cross-region replication and managed vector extensions so AI workloads can live in the same database as core transactional data. If you are building data-intensive products and want to see serverless Postgres in action, book a demo or spin up a free project.