SchemaX

Declarative schema management and migration for Databricks Unity Catalog — design schemas visually, version changes in Git, and deploy consistently across environments.

SchemaX brings schema-as-code to the lakehouse. Define your catalogs, schemas, tables, views, volumes, functions, and governance policies in a visual designer or through the CLI, track every change as a versioned operation, and generate dependency-ordered SQL that deploys cleanly from dev through production.

Why schema management matters

As your lakehouse grows, so does the complexity of managing its structure. Catalogs, schemas, tables, views, grants, tags, row filters, column masks — these accumulate across environments and teams. Without a structured approach:

• Schema changes are ad hoc and hard to audit
• Governance policies drift between dev, test, and production
• Promoting changes across environments means manual SQL and guesswork
• Rolling back a bad deployment is painful or impossible

SchemaX solves this by treating your catalog structure as code — versioned, reviewable, and deployable through the same Git and CI/CD workflows you use for everything else.

Works alongside Spark and Lakeflow Declarative Pipelines

If your tables are created by Spark jobs or DLT pipelines, SchemaX complements that workflow. Use governance-only mode to manage comments, tags, grants, row filters, and column masks on existing objects — without touching CREATE TABLE statements. Your pipelines handle the data; SchemaX handles the governance layer.

Get started

1. Install the extension Extensions (Ctrl+Shift+X / Cmd+Shift+X) → search SchemaX → Install.

2. Open the designer Click the SchemaX icon in the Activity Bar, then Open SchemaX Designer. Or: Command Palette (Ctrl+Shift+P / Cmd+Shift+P) → SchemaX: Open Designer.

3. Design your schema Add catalogs, schemas, and tables. Edit columns, properties, and governance in the detail panels. Create snapshots and generate SQL when ready.

4. Install the CLI (for import, apply, rollback) Command Palette → SchemaX: Install Python SDK, or pip install schemaxpy.

What you can do

Schema design

• Full object hierarchy — Catalogs, schemas, tables, views, volumes, functions, and materialized views
• Column management — Add, rename, reorder, change types, set nullability, comments, and tags
• Table configuration — Delta and Iceberg formats, partitioning, liquid clustering, external tables with storage locations
• View dependencies — Automatic dependency extraction from SQL with correct creation ordering
• Constraints — Primary keys, foreign keys, and check constraints

Data governance

• Grants — GRANT and REVOKE on all securable object types (catalogs through columns)
• Tags — Governance tags on catalogs, schemas, tables, views, and columns
• Row filters — Row-level security policies
• Column masks — Column-level data masking
• Table properties — Delta Lake TBLPROPERTIES configuration
• Bulk operations — Apply the same grant or tag across an entire catalog or schema in one action

Version control and deployment

• Snapshots — Semantic versioned snapshots with changelog tracking
• Environment mapping — Logical catalog names mapped to physical names per environment (dev/test/prod)
• SQL generation — Dependency-ordered, idempotent DDL with environment-specific catalog names
• Apply and rollback — Deploy via Databricks Statement Execution API with deployment tracking
• Safety validation — Operations classified as SAFE, RISKY, or DESTRUCTIVE before rollback
• Governance-only mode — Deploy only governance DDL, skip CREATE statements for pipeline-managed objects
• CI/CD ready — GitHub Actions, GitLab CI, Azure DevOps, and Databricks Asset Bundles integration

Import existing assets

• From Databricks — Import your live Unity Catalog hierarchy into a SchemaX project
• From SQL — Parse DDL files and import the schema structure

Commands

Multi-provider roadmap

SchemaX is built on a provider architecture. Unity Catalog is fully supported today (v0.2.x). Lakebase (PostgreSQL) support is in active development for v0.3.x — same workflow, same Git integration, different catalog system.

Project structure

SchemaX stores project data in a .schemax folder in your workspace:

• project.json — Project configuration and environment settings
• changelog.json — Pending changes (uncommitted operations)
• snapshots/ — Version snapshots (e.g. v0.1.0.json)

Requirements

• VS Code 1.90.0 or newer
• A workspace folder open
• Python SDK (pip install schemaxpy) for import, apply, rollback, and validate

Links

• Documentation — Setup, quickstart, and reference
• Python SDK on PyPI — CLI and automation
• GitHub Repository — Source code and issues
• Report an issue

Apache License 2.0 — see LICENSE for details.