Who needs MLflow when you have SQLite?

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • ploomber

    The fastest ⚑️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

  • Fair point. MLflow has a lot of features to cover the end-to-end dev cycle. This SQLite tracker only covers the experiment tracking part.

    We have another project to cover the orchestration/pipelines aspect: https://github.com/ploomber/ploomber and we have plans to work on the rest of features. For now, we're focusing on those two.

  • ploomber-engine

    A toolbox 🧰 for Jupyter notebooks πŸ“™: testing, experiment tracking, debugging, profiling, and more!

  • If you need help, you can open an issue on GitHub (https://github.com/ploomber/ploomber-engine) or join our Slack! (https://ploomber.io/community/)

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • neptune-client

    πŸ“˜ The MLOps stack component for experiment tracking

  • rubicon-ml

    Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!

  • unionml

    UnionML: the easiest way to build and deploy machine learning microservices

  • Checkout Flyte.org and it’s sibling project https://www.union.ai/unionml

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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