Datatron vs Postman

Compact layout;HTTP requests with file upload support;Formatted API responses for JSON and XML;Image previews;Request history;Basic Auth, OAuth 1.0, OAuth 2.0, and other common auth helpers;Autocomplete for URL and header values;Key/value editors for adding parameters or header values. Works for URL parameters too.;Use environment variables to easily shift between settings. Great for testing production, staging or local setups.;Keyboard shortcuts to maximize your productivity;Automatically generated web documentation;Mock servers hosted on Postman’s cloud;API monitoring run from Postman cloud

Explore models built and uploaded by your Data Science team, all from one centralized repository; Create and scale model deployments in just a few clicks. Deploy models developed in any framework or language; Make better business decisions to save your team time and money. Monitor model performance and detect model decay as it happens; Spend less time on model validation, bias detection, and internal audit processes. Go from model development to internal auditing to production faster than ever; Manage multivariate models through A/B testing for live inference and batch tasks; Apply business logic to your model prediction results. Create workflows for your models using multiple sources and languages