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A data model is an abstract representation of real-world entities. It organizes data elements and their properties and standardizes how they relate.

Data modeling concepts

Learn about the data modeling service (DMS) and core concepts like containers, views, spaces, and instances.

Examples and best practices

Follow recommendations for composing and deploying data models and queries.

Time series integration

Learn how to integrate time series data with your data model.

Files integration

Learn how to integrate files with your data model.

Cognite data models

Explore the Cognite core and industry data models, and understand system limits.

Records and streams

Learn about high-performance storage for bulk structured data using records and streams.

GraphQL interface

Use GraphQL to query, mutate, and define data models in Cognite Data Fusion.

Design with NEAT

Design and validate data models in Excel before deploying them through the Cognite Toolkit. Part of the Deploy tab.

Limits and restrictions

Learn about the limits and restrictions for data modeling resources in your CDF project.

API reference

REST endpoints for Spaces, Instances, Containers, Views, and Data models.
Last modified on September 24, 2026