Hazelcast online store

Description

The Hazelcast online store provides support for materializing feature values into a Hazelcast cluster for serving online features in real-time. In order to use Hazelcast as an online store, you need to have a running Hazelcast cluster. See this getting started page for more details.

Each feature view is mapped one-to-one to a specific Hazelcast IMap
This implementation inherits all strengths of Hazelcast such as high availability, fault-tolerance, and data distribution.
Secure TSL/SSL connection is supported by Hazelcast online store.
You can set TTL (Time-To-Live) setting for your features in Hazelcast cluster.

Each feature view corresponds to an IMap in Hazelcast cluster and the entries in that IMap correspond to features of entities. Each feature value stored separately and can be retrieved individually.

Getting started

In order to use Hazelcast online store, you'll need to run pip install 'feast[hazelcast]'. You can then get started with the command feast init REPO_NAME -t hazelcast.

Examples

{% code title="feature_store.yaml" %}

yaml

project: my_feature_repo
registry: data/registry.db
provider: local
online_store:
  type: hazelcast
  cluster_name: dev
  cluster_members: ["localhost:5701"]
  key_ttl_seconds: 36000

{% endcode %}

Functionality Matrix

	Hazelcast
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	yes
support for deleting expired data	yes
collocated by feature view	no
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.