BentoML vs. MLflow Comparison


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About Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.	About MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Companies, professionals and developers in search of a solution to simplify model deployment	Audience Companies looking for an open source platform solution for the machine learning lifecycle
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing No information available. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information BentoML United States www.bentoml.com	Company Information MLflow Founded: 2018 United States mlflow.org
Alternatives Domino Enterprise AI Platform Domino Data Lab	Alternatives Union Cloud Union.ai
NVIDIA Triton Inference Server NVIDIA	Amazon SageMaker Amazon
Azure Machine Learning Microsoft	ClearML
Huawei Cloud ModelArts Huawei Cloud	Gemini Enterprise Agent Platform Google
Amazon SageMaker Amazon View All	DVC iterative.ai View All
Categories AI Development Supported AI Infrastructure Supported Machine Learning Supported ML Model Deployment Supported	Categories AI Gateways Supported LLM Evaluation Supported Machine Learning Supported ML Experiment Tracking Supported ML Model Deployment Supported ML Model Management Supported

Integrations Amazon SageMaker Supported Apache Spark Supported Docker Supported H2O.ai Supported Keras Supported Kubernetes Supported TensorFlow Supported ZenML Supported Apolo Not Supported Azure Functions Supported Determined AI Not Supported Flyte Not Supported Heroku Supported Kedro Not Supported LiteLLM Not Supported Prometheus Supported Swagger Supported Vectice Not Supported neptune.ai Not Supported Show More Integrations View All 23 Integrations	Integrations Amazon SageMaker Supported Apache Spark Supported Docker Supported H2O.ai Supported Keras Supported Kubernetes Supported TensorFlow Supported ZenML Supported Apolo Supported Azure Functions Not Supported Determined AI Supported Flyte Supported Heroku Not Supported Kedro Supported LiteLLM Supported Prometheus Not Supported Swagger Not Supported Vectice Supported neptune.ai Supported Show More Integrations View All 47 Integrations
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