Test APIs with datasets in Postman
Datasets are available on Postman Solo, Team, and Enterprise plans. For more information, see the pricing page.
Datasets are reusable data sources to manage and use data across your API workflows. Use datasets to run data-driven collection runs, power dynamic mock server responses, and validate API behavior in scripts. By centralizing your data, datasets enable you to reuse the same data across workflows and avoid duplicating or hardcoding values.
Datasets support a variety of workflows, including:
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Data-driven testing — Use datasets as iteration data to run collections with multiple inputs. This enables you to test different scenarios locally, using the CLI, or in CI/CD pipelines.
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Reusable test data — Define your data once and use it across your workspace. This reduces duplication and keeps your data consistent throughout your workspace.
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Test with external data sources — Connect datasets to external sources like MySQL to test against dynamic, large-scale data.
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Separate data from test logic — Keep your collections clean and maintainable. This makes workflows easier to understand, update, and scale.
Create datasets
Create a dataset to define the data you want to use in your workflows. You can add multiple data sources, such as CSV or JSON files and external databases, and define views to retrieve and shape that data.
Learn more at Create datasets.
Manage datasets
As your data and workflows evolve, you can update your datasets by adding or removing data sources and modifying views. This enables you to support new scenarios, combine data from different sources, and control how data is used across your workflows.
Learn more at Manage datasets.
Use datasets
Use datasets across your workflows to run tests, simulate API behavior, and validate responses. You can use datasets as iteration data in collection runs, query them in scripts, and power dynamic responses in mock servers.
Learn more at Use datasets.
Example dataset views
Learn how to write views to filter and combine data from your dataset using SQLite-compatible syntax and functions.
Learn more at Example dataset views.