Summary: A Neon Twin is a full or partial clone of your production or staging database hosted on Neon, giving developers isolated, sandboxed environments that stay automatically synchronized with production. Use a Neon Twin when you want to run development and testing against real schema and data without touching production, with instant branches spun up per developer or feature. Choosing between a full Twin (pg_dump/pg_restore of the entire database) and a partial Twin (schema plus selected tables only) depends on data volume and how much production fidelity your workflow requires.

Learn how to Twin your production database with Neon

Explore our dev/test use case

Move development and testing to Neon; keep production right where it is.Read more about our dev/test use case here.

A Neon Twin is a full or partial clone of your production or staging database, providing developers and teams with isolated, sandboxed environments that closely mirror production.

Creating a Neon Twin will streamline development workflows, enhance productivity, and help teams ship faster, all while being more cost-effective and easier to manage than traditional development/testing environments.

The workflows in this section enable automatic synchronization between your production database and your Neon Twin.

With a Neon Twin created, branches can be quickly spun up or torn down, enabling developers to build new features or debug issues, all within their own isolated environments with a dedicated compute resource.

Branches can be created and managed through the Neon console or programmatically via the API.

Pick the workflow that fits your needs. A full Twin mirrors your entire production database; a partial Twin clones only the schema and selected tables, which is faster and useful when you don't need every row of production data.

• Create a full Twin: Clone your entire production database to Neon using pg_dump and pg_restore in a GitHub Actions workflow.
• Create a partial Twin: Clone only the schema and selected tables from production using pg_dump, pg_restore, and psql.

• Data anonymization

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