Data Views for Data Architecture

Data Views in persistence mode replace traditional static ERD diagrams with an interactive, model-derived approach. Entities appear as nodes on a force-directed graph canvas with edges inferred from foreign key relationships. Click any node to open the Entity Overlay, a floating property table that shows key roles, field names, concrete database types, nullable flags, unique constraints, defaults, FK references, and comments. All entity data comes from the central model (model.neoarc); the view stores only layout positions and profile configuration.

Conceptual, Logical, and Physical Data Views

The same model entities produce different levels of detail depending on how the Data View is configured.

Multiple Data Views from One Model

A project typically maintains several Data Views derived from the same model, each targeting a different database vendor, a different subset of entities, or a different audience.

The Entity Overlay

Click any node on the graph canvas (or press Alt+Enter) to open the Entity Overlay. The overlay is a floating panel that shows the full property table for that entity, with columns determined by the view mode.

Relationship pills on either side of the overlay let you navigate to connected entities. Pin an overlay to dock it below the canvas, then click another node to compare two entities side by side.

Example: E-Commerce Data Model with Two Profiles

Consider an e-commerce model with Customer, Order, OrderItem, Product, and Category entities. Creating two persistence mode Data Views with different database profiles produces vendor-specific physical representations from the same source data. The Entity Overlay for each view shows the resolved types.

Graph Canvas Features

The Data View graph canvas provides interactive tools for exploring the data model.

Fidelity Considerations

Not all abstract types map equally across vendors. When switching a view from one database profile to another, the system checks for fidelity loss and shows a confirmation dialog listing any warnings.

Naming Conventions Across Profiles

Each database profile includes a naming convention that controls how entity and property names are displayed in the Data View. The model stores names in their original format; conversion is applied at display time only.

Using Groups to Organise Views

When the model defines groups (subdomains), the entity picker provides group filtering. This simplifies creating views that focus on a specific domain area. For example, an e-commerce model might have groups for Core Commerce, Product Catalogue, and Logistics, each with a corresponding focused Data View.

SQL DDL Import

The SQL DDL import reads existing database scripts and populates the central model with entities, properties, key roles, and relationships. Paste or upload DDL text from 6 dialects (PostgreSQL, MySQL, SQL Server, Snowflake, Oracle, and DBML). From the imported model, Data Views can be created to visualise the schema interactively.