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Starfish ETL VS Comet.ml

Compare Starfish ETL VS Comet.ml and see what are their differences

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Starfish ETL logo Starfish ETL

The Starfish ETL (Extract Transform Load) Suite is a CRM integration and migration tool.

Comet.ml logo Comet.ml

Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
  • Starfish ETL Landing page
    Landing page //
    2023-10-21
  • Comet.ml Landing page
    Landing page //
    2023-09-16

Starfish ETL videos

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Connector Overview

Comet.ml videos

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Running Effective Machine Learning Teams: Common Issues, Challenges & Solutions | Comet.ml

More videos:

  • Review - Comet.ml - Supercharging Machine Learning

Category Popularity

0-100% (relative to Starfish ETL and Comet.ml)

Starfish ETL

Comet.ml

Data Integration
100 100%
Data Integration
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
ETL
100 100%
ETL
0% 0
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100

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What are some alternatives?

When comparing Starfish ETL and Comet.ml, you can also consider the following products

AWS Glue - Fully managed extract, transform, and load (ETL) service

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

Xplenty - Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.

Weights & Biases - Developer tools for deep learning research

AWS Database Migration Service - AWS Database Migration Service allows you to migrate to AWS quickly and securely. Learn more about the benefits and the key use cases.

Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.

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