What is ADL?
Agnostic Data Labs (ADL) is a tool for data teams who are tired of writing the same boilerplate code over and over again.
If you've ever built a data warehouse, a staging area, or a data vault, you know the drill — dozens of tables, hundreds of columns, and a mountain of repetitive SQL that all follows the same patterns. ADL takes a different approach: define your metadata once, pair it with templates, and generate everything you need.
ADL runs in your browser. There's no database to install, no server to manage, and no special tools to set up — just a local folder and a modern browser. Your metadata stays on your own machine, in your own repository.
How it works
ADL is built around three simple ideas.
1. Metadata — describe what you have
Your data solution starts with metadata. In ADL, this means defining your data connections (where your data lives), data objects (your tables, views, and queries), and how they relate to each other through mappings.
All metadata is stored as plain JSON files using an open-source schema. There's no proprietary format and no database to manage — just files in your repository that you can edit in ADL or any text editor.
2. Templates — describe what you want
Templates define the output you want to generate. They're written in Handlebars, a straightforward templating language that's easy to pick up even if you've never used it before.
A template might generate a SQL CREATE TABLE statement, a stored procedure, a Markdown documentation page, or a deployment script. ADL comes with a library of ready-made templates for common patterns, and you can create your own for anything else.
3. Output — generate and deploy
When you combine metadata with templates, ADL generates your output files — SQL scripts, documentation, configuration files, or whatever your templates produce. Each template generates one output file per mapped metadata object, so everything stays organised and predictable.
The generated files land in your repository, ready to be reviewed, committed, and deployed through your normal CI/CD pipeline.
Why ADL?
- Save time. Stop hand-writing the same SQL patterns for every table. Define the pattern once as a template and let ADL do the rest.
- Stay consistent. When every script is generated from the same template, you know they all follow the same standards and conventions.
- Stay flexible. Your metadata and templates are plain files in your repo. There's no vendor lock-in, no proprietary database, and no special tools required to read or edit them.
- Work with any platform. ADL supports SQL Server, Snowflake, PostgreSQL, and more. Your templates can generate output for any target.
- Evolve with confidence. Need to change a pattern across 200 tables? Update the template and regenerate. Done.
What you get
Your metadata is stored as open-format JSON files in your own repository. Your templates use an open-source language. Everything stays portable and under your control.
SQL Server, Snowflake, PostgreSQL — ADL doesn't care where your data lives. Define connections to any platform and generate output tailored to each one.
All metadata and templates live as files in your repo. Use your normal branching, code review, and CI/CD workflows — nothing changes about how your team works.
Flexibility can be powerful, but also overwhelming at first. ADL ships with starter architectures for common scenarios — conceptual or logical designs, Data Vault, Persistent Staging Areas, and more. Customise them, or build your own from scratch.
What's in the box
ADL ships with ready-to-run starter solutions for common patterns. Install one from the Marketplace and you get pre-configured metadata, templates, and conventions — open the project and start generating immediately.
- Data Vault Virtual DW — views-based integration and presentation layers.
- Persistent Staging Area — delta detection adapted for Snowflake.
- Data Vault Physical DW — materialised tables on SQL Server.
- Data Vault Virtual DW — 3-tiered, views-based.
- Persistent Staging Area — stored-procedure delta detection.
- Metadata Architecture — how to structure metadata for a data solution.
- NBility — a business capability reference model.
Each sample is fully inspectable in the docs — see the Sample Designs reference for deep dives.
Get started
ADL is free in public preview. The quickest path is to install a starter solution from the Marketplace, run the generator, and see real output land in your repository within minutes.
- Try the app — free, no signup hurdles.
- Quick Start Guide — set up your first project in a few minutes.
- How ADL Works — the workflow in detail.