The Bigtable online store provides support for materializing feature values into Cloud Bigtable. The data model used to store feature values in Bigtable is described in more detail here.
In order to use this online store, you'll need to run pip install 'feast[gcp]'. You
can then get started with the command feast init REPO_NAME -t gcp.
{% code title="feature_store.yaml" %}
project: my_feature_repo
registry: data/registry.db
provider: gcp
online_store:
type: bigtable
project_id: my_gcp_project
instance: my_bigtable_instance{% endcode %}
The full set of configuration options is available in BigtableOnlineStoreConfig.
The set of functionality supported by online stores is described in detail here. Below is a matrix indicating which functionality is supported by the Bigtable online store.
| Bigtable | |
|---|---|
| write feature values to the online store | yes |
| read feature values from the online store | yes |
| update infrastructure (e.g. tables) in the online store | yes |
| teardown infrastructure (e.g. tables) in the online store | yes |
| generate a plan of infrastructure changes | no |
| support for on-demand transforms | yes |
| readable by Python SDK | yes |
| readable by Java | no |
| readable by Go | no |
| support for entityless feature views | yes |
| support for concurrent writing to the same key | yes |
| support for ttl (time to live) at retrieval | no |
| support for deleting expired data | no |
| collocated by feature view | yes |
| collocated by feature service | no |
| collocated by entity key | yes |
To compare this set of functionality against other online stores, please see the full functionality matrix.