---
title: "Enabling Evolutionary Database Development: database branching with Lakebase"
description: "Evolutionary database development treats migrations as first-class CI/CD artifacts, but shared development databases still limit per-developer isolation and fast, realistic feedback. The post follows Jen as she adds location, batch, and serial fields to inventory, coordinating application changes, production-data preservation, schema migration, and tests for storing, reading, and displaying the new values. It contrasts shared databases and simplified local substitutes with Databricks Lakebase copy-on-write branches, created in one second with zero storage at creation, including for a terabyte-scale production database. Jen pairs code and database branches, while CI creates a temporary branch, validates an idempotent and reversible migration, runs application and database tests, and posts a schema diff, enabling combined review and shifting DBA attention toward design and maintainability."
---

# Enabling Evolutionary Database Development: database branching with Lakebase

[Databricks](https://yomu.fyi/company/databricks) · Pramod Sadalage, Kevin Hartman · May 29, 2026

**Type:** Explainer

## Summary

Evolutionary database development treats migrations as first-class CI/CD artifacts, but shared development databases still limit per-developer isolation and fast, realistic feedback. The post follows Jen as she adds location, batch, and serial fields to inventory, coordinating application changes, production-data preservation, schema migration, and tests for storing, reading, and displaying the new values. It contrasts shared databases and simplified local substitutes with Databricks Lakebase copy-on-write branches, created in one second with zero storage at creation, including for a terabyte-scale production database. Jen pairs code and database branches, while CI creates a temporary branch, validates an idempotent and reversible migration, runs application and database tests, and posts a schema diff, enabling combined review and shifting DBA attention toward design and maintainability.

## Context

Shared development databases make database changes risky and slow because developers can interfere with one another, must coordinate access, or rely on stale or dialect-mismatched local substitutes. This limits fast, realistic feedback and leaves per-developer production-shaped databases largely aspirational.

## Approach / What changed

Use Databricks Lakebase copy-on-write database branches alongside code branches. Developers work against isolated production-shaped databases, while CI creates temporary branches to apply and validate migrations, run application and database tests, and publish schema differences for pull-request review.

## Takeaways

- Lakebase branches provide isolated database environments without requiring developers to wait for or coordinate access to a shared development database.
- CI can validate a migration by applying it to a temporary Lakebase branch, checking that it is clean, idempotent, and reversible, and running tests against the migrated schema.
- The workflow lets DBAs review schema design, data integrity, indexing, extensibility, and maintainability instead of serving primarily as a synchronous gate against shared-database breakage.

**Tags:** [CI/CD](https://yomu.fyi/topic/ci-cd), [Databases](https://yomu.fyi/topic/databases), [Lakebase](https://yomu.fyi/topic/lakebase)

- Source: [Databricks](https://www.databricks.com/blog/enabling-evolutionary-database-development-database-branching-lakebase)
- Source URL: https://www.databricks.com/blog/enabling-evolutionary-database-development-database-branching-lakebase
- Ingested by Yomu: 2026-08-31T03:32:34.188Z

[Read original post](https://www.databricks.com/blog/enabling-evolutionary-database-development-database-branching-lakebase)