Who needs MLflow when you have SQLite?

1. ploomber

   1 121 3,557 6.4 Python

   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.

2. Judoscale

   judoscale.com featured

   Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.

   

3. ploomber-engine

   2 3 68 5.5 Python

   Discontinued A toolbox 🧰 for Jupyter notebooks 📙: 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/)

4. neptune-client

   3 26 613 8.1 Python

   📘 The experiment tracker for foundation model training

   

5. rubicon-ml

   4 1 131 7.4 Jupyter Notebook

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

   

6. unionml

   5 6 337 4.0 Python

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

   

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

7. InfluxDB

   influxdata.com featured

   InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.

   

Suggest a related project