This content originally appeared on DEV Community and was authored by Bobur Umurzokov
Learn how to create schema-only database environments to work with sensitive data and make zero-risk schema changes.
Why do you need multiple databases for development?
Working on a live production database during development is risky. Even the smallest mistake like dropping a column or applying an incorrect migration can lead to downtime, corrupted data, or data loss. That’s why modern teams isolate their environments: you might have a separate dev, staging, and prod database to protect production while still iterating fast.
By working in an isolated environment, you get:
- A safe space to develop new features
- No risk of affecting real user data
- The freedom to experiment with schema changes
- The ability to test integrations without breaking anything critical
Benefits of syncing only the schema
But in most cases, when you are creating a new database environment, you just want to sync the schema but not the data because of:
- Compliance: You avoid sharing real customer data across environments.
- Safety: Developers can’t accidentally query or mutate production data.
- Speed: Schema deployments are lightweight and fast—no data copy or replication overhead.
- Control: You can generate and populate a test environment with randomized or anonymized data.
This approach is ideal for GDPR-compliant workflows, regulated industries, and teams that care about velocity without compromising on security.
See the short demo of how to create schema-only database environment using GibsonAI.
What is GibsonAI?
GibsonAI is your AI-powered “database engineer” that lets you design, build, deploy, and scale production-ready serverless databases using natural-language prompts.
You can create a database schema for your new project idea using the GibsonAI App by chatting with AI. Under the hood, GibsonAI spun up a new real MySQL/Postgres database. You can create multiple database environments and update the existing schema in AI chat.
How GibsonAI Schema First Approach Works
When you define first time your database schema in the GibsonAI project, that schema becomes the source of truth for ongoing development. It is called Current Schema, and it is a safe environment where you can update or run experiments by chatting with AI. Once you are confident, you can then provision that schema to any number of databases, like prod, staging, or feat-a.
This way, each database receives the same structure, but not the same data, allowing you to test, build, or ship new features using safe, synthetic, or anonymized datasets. GibsonAI makes working with multiple database environments safe. You can see difference between the current state of the schema and deployed one in the same dashboard.
How to Create and Work with a Schema-only Environment in GibsonAI
You can create a schema-only database environment in the GibsonAI App. Imagine you’re a developer building a new feature for a travel agency app. You’re adding a new trip_preferences table into the existing database, and you want to test this schema without touching the production database and its data.
Here’s how to do it with GibsonAI:
1. Select Your Project
Open the GibsonAI App and pick the project you’re actively working on.
2. Go to Databases and Create a New Database
Head over to the Databases tab. Click Create Database, and name it something like feat-a. This becomes your feature database environment.
Newly created database has not any database schema initially. You will get empty database. But the Current schema keeps current state of the schema you are working on.
3. Update the Current Schema
Use the Schema Editor or chat with GibsonAI to add new tables, columns, or relationships—like trip_preferences.
Your schema updates live inside your project, not in the database itself. This ensures changes stay tracked and reproducible.
4. Deploy Schema to feat-a
Click Deploy to Database and choose your newly created feat-a database. GibsonAI will provision the latest schema structure only into the environment. You can now use AI chat to generate sample SQL insert queries to populate with data.
5. Deploy to Production When Ready
Once you’re confident, deploy the same schema to the production database. Since GibsonAI doesn’t automatically sync changes between environments. You control where and when to apply the schema. This gives you the ability to test fearlessly—and ship confidently.
Summary
Schema-only database environments in GibsonAI give you a production-like structure without exposing production data. Whether you’re fixing a bug, testing a new feature, or validating complex changes, you can work in isolation and still deploy with confidence.
By separating structure from data, GibsonAI empowers your team to:
- Move fast without breaking production
- Work safely in parallel
- Stay compliant and secure
This content originally appeared on DEV Community and was authored by Bobur Umurzokov