Who is this for?
All new customers and existing customers building next-generation solutions using CDF’s industrial knowledge graph. In data modeling, assets are represented as instances using the CogniteAsset concept in the core data model—with support for hierarchies, relations, and flexible schemas. To learn more about data modeling for the knowledge graph, see the Data modeling section.Choose your path
I'm building applications
Use REST and GraphQL APIs to query and mutate data. Start with the GraphQL schema service and Query features.
I'm designing data pipelines
Define schemas, ingest data, and build high-volume pipelines. Start with Containers and views, Ingestion, and Records and streams.
Key APIs
- Spaces — Define data boundaries. See Spaces and instances.
- Instances — Nodes and edges. See Query features.
- Containers — Schema definitions. See Containers and views.
- Views — Queryable projections. See Containers and views.
- Data models — Grouped views. See Data models.
Reference
- Examples and best practices — Building asset hierarchies, extending the core model, integrations, performance, and CI/CD.
- Limits and restrictions — Resource limits, property value limits, and concurrency for data modeling.
- Core data model — CogniteCore building blocks (Asset, TimeSeries, File, and more).
- Process industries data model — CogniteProcessIndustries extension for maintenance orders, operations, and notifications.
Data-plane APIs
When working with industrial data through data modeling, you also use these APIs for the underlying data operations:Time series and datapoints
Insert, retrieve, and query time series datapoints.
Datapoints
Insert, retrieve, and delete data points in time series.
File content
Upload and download file content.