DataM8 helps teams build and evolve data platforms through metadata-driven code generation. Describe your data structures and transformations once, then combine them with reusable templates to generate consistent target artifacts.
Developed by ORAYLIS, DataM8 brings together a visual editor, an extensible metadata model and a command-line generator — helping teams spend less time on repetitive implementation and more time delivering business value.
This repository is the product overview and English user handbook. You do not need to build DataM8 from source to use the app or CLI.
| I want to… | Begin here | First result |
|---|---|---|
| Edit a model visually | Install the app, then open a sample copy | Change a description, reload it and generate model documentation |
| Maintain models or automate generation from the command line | Install the CLI, then validate and generate | Validate a local solution and inspect freshly generated files |
| Adapt templates and target conventions | Automation concepts and template development | Change one template on a disposable sample and inspect its output |
| Develop a source connector | Build a connector | Import static metadata using the runnable offline example |
| Improve the editor, backend or schemas | Choose the owning repository and contribution workflow | Set up the relevant component and run its focused checks |
Recommended first exercise: use the app with a disposable sample copy, edit
Customer, verify save/reload and generate docs. The tutorial records its exact
capture revisions; release-specific compatibility is
documented with the selected release. Generating files does not deploy or execute
them on a data platform.
- Faster development: generate repetitive code from metadata and focus on business logic.
- Reusable standards: capture your team's conventions in templates and share them across projects.
- Consistent results: validate models and generate artifacts through a common process.
- Central maintenance: evolve shared templates and regenerate the affected artifacts.
- Documentation from metadata: keep generated model documentation aligned with the same metadata that drives your code.
Open the overview at full resolution to read the diagram labels on smaller screens.
DataM8 puts metadata at the center of automation. Describe data sources, structures and transformations in a model, maintain it with the editor or your development tools, and combine it with target-specific templates to generate artifacts for your data platform.
The illustration shows the conceptual ORAYLIS Automation workflow. Source metadata import depends on the available connectors; supported platforms and target behavior are described in the component references and sample documentation.
| Component | What it does | Repository |
|---|---|---|
| Frontend | Visually edit models and manage solutions in the web editor or desktop application. | datam8-frontend |
| CLI / Generator | Validate models and generate target artifacts from templates; provide the editor's backend. | datam8-cli |
| Metadata Model | Define the shared model structure and JSON schemas used by the editor and generator. | datam8-model |
| Sample Solution | Explore a concrete model with templates, properties and example targets. | datam8-sample-solution |
This repository is the central home for the product overview and user handbook. See repository responsibilities for technical references and contribution routes.
Open the generator diagram at full resolution to inspect the artifact types.
Templates turn a shared metadata model into artifacts suited to your target technology. You can adapt the templates to your architecture and conventions, then inspect and version the generated output using your usual development tools.
The diagram illustrates possible artifact types; the original label "Doku" means documentation. The sample target reference describes the targets actually included in the sample. Generation writes files; deployment and execution are subsequent steps in your platform's workflow.
Both diagrams are taken from the ORAYLIS Automation pitch. See illustration sources for provenance.
Use the documentation index for all topics. This documentation covers DataM8 v2. Start with the current stable app or CLI release linked from installation. Release notes describe version-specific requirements; historical capture evidence records the separate revisions used for the illustrated tutorial.
Issues are tracked here. Include the component and exact versions using the issue form. For sensitive reports, use the security reporting route.