MLflow VS Sacred

Compare MLflow vs Sacred and see what are their differences.

MLflow

Open source platform for the machine learning lifecycle (by mlflow)

Sacred

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA. (by IDSIA)
Our great sponsors
  • SonarQube - Static code analysis for 29 languages.
  • OPS - Build and Run Open Source Unikernels
  • Scout APM - Less time debugging, more time building
MLflow Sacred
22 4
11,127 3,703
3.3% 1.1%
9.7 4.5
6 days ago about 2 months ago
Python Python
Apache License 2.0 MIT License
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.

MLflow

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 2022-01-21.

Sacred

Posts with mentions or reviews of Sacred. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-26.

What are some alternatives?

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

dvc - πŸ¦‰Data Version Control | Git for Data & Models | ML Experiments Management

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

zenml - ZenML πŸ™: MLOps framework to create reproducible pipelines.

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

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

tensorflow - An Open Source Machine Learning Framework for Everyone

guildai - Experiment tracking, ML developer tools

neptune-client - Neptune client library - integrate your Python scripts with Neptune

gensim - Topic Modelling for Humans

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

pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator