machine-learning-platforms-compared.md

Features	AWS	GCP	Azure	Databricks
Data pipeline	Data Pipeline	Dataflow	Data Factory	Spark
Feature Store	Feature Store	---	---	Feature Store
Model Monitoring	Model Monitor	---	Azure Monitor	---
Experiment Management	SageMaker Experiments	---	Azure Machine Learning SDK	MLFlow Tracking
Model versioning	Production Variants	Versions	Model registration	MLflow Model Registry
A/B Testing	Sagemaker	---	Controlled Rollout	---
Model Serving	Sagemaker	AI Platform	Azure Machine Learning	MLFlow Model Serving
AutoML	Autopilot	Cloud AutoML	AutomatedML	Databricks AutoML
Notebooks	Sagemaker Notebooks	AI Platform Notebooks	Microsoft Azure Notebooks	Notebooks

Table used in my article on TWD https://towardsdatascience.com/end-to-end-machine-learning-platforms-compared-c530d626151b

https://aws.amazon.com/about-aws/whats-new/2020/12/introducing-amazon-sagemaker-feature-store/

Hi Ash, thanks for putting up this comparison. This is quite good, I am writing an article on Feature Stores as well, can I back-link this image of yours?

Go for it @pronojitsaha

Needs an update tbh as i've not touched it in some time.

Features stores seem to be now more broadly available:
Databricks: https://docs.databricks.com/applications/machine-learning/feature-store/index.html
Google: https://cloud.google.com/vertex-ai/docs/featurestore

Model monitoring also in Google: https://cloud.google.com/vertex-ai/docs/model-monitoring

AutoML in Databricks: https://databricks.com/de/product/automl

Experimentation in Google: https://cloud.google.com/vertex-ai/docs/experiments/tensorboard-overview