Prophet VS MLflow

Compare Prophet vs MLflow and see what are their differences.


Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. (by facebook)


Open source platform for the machine learning lifecycle (by mlflow)
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Prophet MLflow
214 48
15,940 14,441
1.5% 3.6%
8.5 9.9
1 day ago 4 days 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.


Posts with mentions or reviews of Prophet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-15.


Posts with mentions or reviews of MLflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-14.
  • Options for configuration of python libraries - Stack Overflow
    2 projects | | 14 May 2023
    In search for a tool that needs comparable configuration I looked into mlflow and found this. There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
  • [D] Is there a tool to keep track of my ML experiments?
    2 projects | | 13 May 2023
    I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
  • Looking for recommendations to monitor / detect data drifts over time
    3 projects | | 15 Apr 2023
    Dumb question, how does this lib compare to other libs like MLFlow,
  • Integrating Hugging Face Transformers & DagsHub
    2 projects | | 27 Mar 2023
    While Transformers already includes integration with MLflow, users still have to provide their own MLflow server, either locally or on a Cloud provider. And that can be a bit of a pain.
  • Any MLOps platform you use?
    5 projects | | 25 Feb 2023
    I have an old labmate who uses a similar setup with MLFlow and can endorse it.
    3 projects | | 25 Feb 2023
    MLflow - an open-source platform for managing your ML lifecycle. What’s great is that they also support popular Python libraries like TensorFlow, PyTorch, scikit-learn, and R.
  • Selfhosted chatGPT with local contente
    3 projects | | 24 Feb 2023
    even for people who don't have an ML background there's now a lot of very fully-featured model deployment environments that allow self-hosting (kubeflow has a good self-hosting option, as do mlflow and metaflow), handle most of the complicated stuff involved in just deploying an individual model, and work pretty well off the shelf.
  • ML experiment tracking with DagsHub, MLFlow, and DVC
    4 projects | | 12 Jan 2023
    Here, we’ll implement the experimentation workflow using DagsHub, Google Colab, MLflow, and data version control (DVC). We’ll focus on how to do this without diving deep into the technicalities of building or designing a workbench from scratch. Going that route might increase the complexity involved, especially if you are in the early stages of understanding ML workflows, just working on a small project, or trying to implement a proof of concept.
  • AI in DevOps?
    2 projects | | 6 Dec 2022
  • AWS re:invent 2022 wish list
    2 projects | | 23 Nov 2022
    I am seeing growing demand for MLflow ( and I am seeing a lot of people looking at Databricks as commercial offering for MLflow. Alternatively, some popele are implementing something like Managing your Machine Learning lifecycle with MLflow. Therefore, I think this was on my wish list last year, but I really hope AWS announce a Managed MLFlow Service. I know version 2.X is too new but at least 1.X would be great start.

What are some alternatives?

When comparing Prophet and MLflow you can also consider the following projects:

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

tensorflow - An Open Source Machine Learning Framework for Everyone

Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

darts - A python library for user-friendly forecasting and anomaly detection on time series.

zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines.

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

scikit-learn - scikit-learn: machine learning in Python

greykite - A flexible, intuitive and fast forecasting library

guildai - Experiment tracking, ML developer tools

dvc - 🦉 Data Version Control | Git for Data & Models | ML Experiments Management

neptune-client - :ledger: Experiment tracking tool and model registry