Bottle vs. Echo vs. MicroPython vs. Modelbit Comparison Chart

High-performance, extensible, minimalist Go web framework. Highly optimized HTTP router with zero dynamic memory allocation which smartly prioritizes routes. Build robust and scalable RESTful API, easily organized into groups. Automatically install TLS certificates from Let's Encrypt. HTTP/2 support improves speed and provides a better user experience. Many built-in middleware to use, or define your own. Middleware can be set at root, group, or route level. Data binding for HTTP request payload, including JSON, XML or form data. API to send a variety of HTTP responses, including JSON, XML, HTML, file, attachment, inline, stream, or blob. Template rendering using any template engine. Customized central HTTP error handling. Easily extendable API. Optimized HTTP router which smartly prioritizes routes. Build robust and scalable RESTful APIs. Extensible middleware framework. Define middleware at root, group, or route level Data binding for JSON, XML, and form payload.

Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built.