ByteHub Cloud works in exactly the same way as the open-source feature store, except that any features you create are stored on a managed cloud account. This allows you to easily store timeseries features for your models without having to worry about setting up database, cloud storage buckets etc.
To get started with ByteHub Cloud contact us to register for an account.
In Python, install using:
pip install bytehub[cloud]
Then login to the feature store by running:
fs = CloudFeatureStore()
You'll be prompted to login and paste an authentication code into Python. At this point you will have a CloudFeatureStore object that allows you to create, transform and load features in exactly the same way as the other tutorials. All of your data will be saved into a private AWS S3 storage bucket, allowing you to share and reuse features easily between sessions.