MLflow vs. MLlib Comparison


MLflow	MLlib Apache Software Foundation	+	+
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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.	About Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem.
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	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 looking for an open source platform solution for the machine learning lifecycle	Audience Data scientists and engineers wanting a machine learning solution for efficient data processing and analysis within the Apache Spark framework
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not 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 Supported Live Online Not Supported In Person Supported
Company Information MLflow Founded: 2018 United States mlflow.org	Company Information Apache Software Foundation Founded: 1995 United States spark.apache.org/mllib/
Alternatives Union Cloud Union.ai	Alternatives Apache Spark Apache Software Foundation
Amazon SageMaker Amazon	Apache PredictionIO Apache
ClearML	Apache Mahout Apache Software Foundation
Gemini Enterprise Agent Platform Google	Amazon EMR Amazon
DVC iterative.ai View All	PySpark View All
Categories AI Gateways Supported LLM Evaluation Supported Machine Learning Supported ML Experiment Tracking Supported ML Model Deployment Supported ML Model Management Supported	Categories Machine Learning Supported

Integrations Apache Spark Supported Kubernetes Supported Amazon SageMaker Supported Apache Cassandra Not Supported Apache HBase Not Supported Axolotl Supported Dagster Supported Databricks Supported Flyte Supported IBM watsonx.data integration Supported Kedro Supported Ludwig Supported OpenMetadata Supported Ragas Supported RapidSOS Supported Superwise Supported TrueFoundry Supported navio Supported neptune.ai Supported Show More Integrations View All 47 Integrations	Integrations Apache Spark Supported Kubernetes Supported Amazon SageMaker Not Supported Apache Cassandra Supported Apache HBase Supported Axolotl Not Supported Dagster Not Supported Databricks Not Supported Flyte Not Supported IBM watsonx.data integration Not Supported Kedro Not Supported Ludwig Not Supported OpenMetadata Not Supported Ragas Not Supported RapidSOS Not Supported Superwise Not Supported TrueFoundry Not Supported navio Not Supported neptune.ai Not Supported Show More Integrations View All 13 Integrations
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