Showing 1–20 of 39 dossiers

Buttondown cut its database from 2TB to 750GB by deleting three legacy tables

Buttondown’s 'Great Pruning' is a small-SaaS operations story about deleting architecture rather than adding it. The company removed duplicated or over-retained request and email-event data after changing how those workloads were processed.

Cloudflare makes Python Workers GA — with Hyperdrive and first-class platform bindings

The Hyperdrive integration was the practical database unlock; the larger September 21 change is that Python Workers themselves are now GA. Cloudflare is explicitly positioning Python as a production language on Workers, with native platform bindings and framework support rather than an experimental compatibility layer.

Railway makes Postgres recovery, HA and pooling machine-operable from its CLI

Agents and operations tooling can inspect HA health, trigger switchovers, restore to a timestamp and change connection pooling from one machine-readable surface. That increases automation power, but recovery actions still create real operational boundaries such as brief failover interruption and forked PITR services.

Pantheon starts moving existing WordPress and Drupal sites off its Valhalla filesystem

This is a platform architecture migration rather than a user-facing feature. Pantheon says no action is required, but builders operating storage-sensitive WordPress or Drupal workloads should know when their tier moves and verify backup, restore and file-handling behavior around the change.

Data systems are difficult to replace precisely because they hold the part of an application that must survive. New databases and managed storage products can remove operational work, but compatibility, consistency, backup behaviour, egress and pricing matter more than a clean getting-started example.

This page follows consequential changes across relational databases, document stores, object storage and managed data platforms. BTN reads the technical details and looks at migration, failure recovery and the long-term cost of keeping data useful. Coverage is aimed at builders choosing a dependable default or evaluating a genuine new capability, not collecting database categories for their own sake.

The beat also covers replication, local-first systems and developer-friendly database services when they create a meaningful new option. Claims about effortless scale are checked against consistency, tooling and recovery. The safest data platform is often the one whose behaviour a team can explain during an ordinary failure.