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  5. How does Tracer Server compare to Autodesk’s AEC Data Model API?

How does Tracer Server compare to Autodesk’s AEC Data Model API?

Autodesk’s AEC Data Model API provides routes to query data about elements inside models stored in a customer’s ACC Hub. Tracer Server is an on-premises technology stack by Proving Ground to leverage Revit’s desktop application for more robust extraction of data from Revit models. These two systems differ in what data is accessible and how the data is provided to an end user.

PG – Tracer ServerADSK – AEC Data Model API
Method:
Uses Revit’s desktop application API for full access to model
Model data access:
Elements are filtered by category
All element parameters are accessible, anything “scheduleable” in Revit is accessible.
2D outlines (areas, rooms, spaces), 2D placement points (most placed instances) are stored as GeoJSON
3D geometry (most placed instances) is stored in gLTF format
Project Information, Worksets, and Warnings are accessible.
Method:
Uses ACC’s API
Model data access:
Series of API endpoints are used to find hubs, find projects, filter elements, find element groups, and/or access schedules within a single model
GraphQL is used to structure requests
Parameter/properties are explicitly queried
Output:
Data is stored in an on-premises relational database schema
Multiple models and their elements exist within a single database
Revit Schedules can be reverse-engineered via a query and view
Database queries and views provide customized output (schedule data, count, averages, geometry, etc)
2D and 3D visuals for Power BI rely on output data, not a cloud viewer.
Output:
Individual JSON responses for each model, not related to data from other models
Limitations:
Data within linked model(s) is not accessible, only the opened document
Noting an instance as “modeled in-place” is not yet accessible.
Limitations:
Data within a linked model is not accessible, only the specified model
Geometry is not available (2D and 3D)
Additional exploration needed to determine if  certain element properties, like “modeled in-place”, are accessible
Data collection into a database or built-in ETL is not provided
Outcomes:
All parameter data on elements are pulled en masse, queries and views are used to filter
Database natively provided
Outcomes:
GraphQL pulls element and property data as defined
Downstream storage or data flow required

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