Test APIs with datasets in Postman

With Postman Datasets, you can manage and reuse data across your API workflows. A dataset is a reusable, queryable data source, so you can define your data once and use it consistently instead of duplicating or hard-coding values.

You can start a dataset from a data file you’d otherwise attach directly, or create one from scratch. Datasets unlock the capabilities below.

Why use datasets

• No file size limits — Unlike a static data file that you upload for each run, a dataset scales from large local files to live databases.
• Data-driven testing — Use a dataset as iteration data to run a collection with many inputs, locally, in the Postman Cloud, from the CLI, or in CI/CD.
• Reuse across workflows — Define your data once and use the same dataset in collection runs, performance tests, mock servers, monitors, and scripts, instead of uploading a separate file to each.
• SQL querying — Shape data with SQLite-compatible views to filter, combine, and transform rows for specific scenarios, without changing the source data.
• Live data sources — Connect to MySQL, Postgres, SQL Server, or any database with a JDBC driver, to test against current data instead of a static snapshot.
• Combine multiple sources — Bring together several data sources in one dataset, including data files (CSV, JSON, and spreadsheets) and live databases, then query across them with views.
• Iteration control — Choose how rows map to iterations and virtual users with iteration strategies.
• Version control — In Local View, each dataset is a YAML file in your Git repository, so changes are reviewable and shareable.

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, JSON, or spreadsheet files, external data sources, or AI-generated data files, 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.