dephell VS BentoML

Compare dephell vs BentoML and see what are their differences.

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dephell BentoML
5 16
1,668 6,441
- 3.5%
7.6 9.8
about 3 years ago about 18 hours ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

dephell

Posts with mentions or reviews of dephell. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-09.

BentoML

Posts with mentions or reviews of BentoML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-04.

What are some alternatives?

When comparing dephell and BentoML you can also consider the following projects:

fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production

seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

PDM - A modern Python package and dependency manager supporting the latest PEP standards

kubeflow - Machine Learning Toolkit for Kubernetes

streamlit - Streamlit — A faster way to build and share data apps.

conda - A system-level, binary package and environment manager running on all major operating systems and platforms.

Flask - The Python micro framework for building web applications.

pip-tools - A set of tools to keep your pinned Python dependencies fresh.

Poetry - Python packaging and dependency management made easy