The Redis online store provides support for materializing feature values into Redis.
Both Redis and Redis Cluster are supported.
The data model used to store feature values in Redis is described in more detail here.
In order to use this online store, you'll need to install the redis extra (along with the dependency needed for the offline store of choice). E.g.
pip install 'feast[gcp, redis]'
pip install 'feast[snowflake, redis]'
pip install 'feast[aws, redis]'
pip install 'feast[azure, redis]'
You can get started by using any of the other templates (e.g. feast init -t gcp
or feast init -t snowflake
or feast init -t aws
), and then swapping in Redis as the online store as seen below in the examples.
Connecting to a single Redis instance:
Connecting to a Redis Cluster with SSL enabled and password authentication:
Additionally, the redis online store also supports automatically deleting data via a TTL mechanism. The TTL is applied at the entity level, so feature values from any associated feature views for an entity are removed together. This TTL can be set in the feature_store.yaml
, using the key_ttl_seconds
field in the online store. For example:
The full set of configuration options is available in RedisOnlineStoreConfig.
The set of functionality supported by online stores is described in detail here. Below is a matrix indicating which functionality is supported by the Redis online store.
To compare this set of functionality against other online stores, please see the full functionality matrix.
Redis | |
---|---|
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
yes
readable by Go
yes
support for entityless feature views
yes
support for concurrent writing to the same key
yes
support for ttl (time to live) at retrieval
yes
support for deleting expired data
yes
collocated by feature view
no
collocated by feature service
no
collocated by entity key
yes