Backwrite vs PostgreSQL: platform and database engine
Backwrite builds on PostgreSQL. Evaluate the surrounding platform workflow and operational cost alongside the database engine, using the same workload and security requirements.
What each layer provides
PostgreSQL provides SQL, transactions, indexes, constraints, access controls, replication, and database extension mechanisms. Backwrite adds documented project and branch orchestration, gateway APIs, and developer tooling around that database engine.
| Decision | PostgreSQL engine | Backwrite platform |
|---|---|---|
| Relational data | SQL, constraints, indexes, and transactions | Uses PostgreSQL for relational storage |
| Environment workflow | Manage databases and deployment tooling | Documented project branches and lifecycle operations |
| Developer access | Database clients and role privileges | Gateway, CLI, SDK, and MCP workflows |
| Messaging and object storage | Integrate additional systems as needed | Documented JetStream and S3-compatible integrations |
When direct PostgreSQL is a good fit
Choose direct PostgreSQL when existing infrastructure already covers provisioning, environments, authentication, storage, and migrations. Keep control over those integrations and measure the effort required to maintain them.
When to evaluate Backwrite
Evaluate Backwrite when a team needs consistent project and branch workflows plus API and agent tooling. Verify the services and creation modes available in the intended deployment rather than inferring availability from an architecture diagram.
Run a reproducible comparison
Use the same schema, dataset, query mix, hardware class, concurrency, and transaction settings. Measure latency percentiles, throughput, provisioning time, failure recovery, and operator effort. Publish configuration and method alongside results; no performance winner is claimed here.