PostgreSQL online store
Description
The PostgreSQL online store provides support for materializing feature values into a PostgreSQL database for serving online features.
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Only the latest feature values are persisted
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sslmodedefaults torequire, which encrypts the connection without certificate verification. To disable SSL (e.g. for local development), setsslmode: disable. For certificate verification, setsslmodetoverify-caorverify-fulland provide the correspondingsslrootcert_path(and optionallysslcert_pathandsslkey_pathfor mutual TLS)
Getting started
In order to use this online store, you'll need to run pip install 'feast[postgres]'. You can get started by then running feast init -t postgres.
Example
{% code title="feature_store.yaml" %}
project: my_feature_repo registry: data/registry.db provider: local online_store: type: postgres host: DB_HOST port: DB_PORT database: DB_NAME db_schema: DB_SCHEMA user: DB_USERNAME password: DB_PASSWORD sslmode: verify-ca sslkey_path: /path/to/client-key.pem sslcert_path: /path/to/client-cert.pem sslrootcert_path: /path/to/server-ca.pem vector_enabled: false
{% endcode %}
The full set of configuration options is available in PostgreSQLOnlineStoreConfig.
Functionality Matrix
The set of functionality supported by online stores is described in detail here. Below is a matrix indicating which functionality is supported by the Postgres online store.
| Postgres | |
|---|---|
| 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 | no |
| 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 | no |
To compare this set of functionality against other online stores, please see the full functionality matrix.
PGVector
The Postgres online store supports the use of PGVector for storing feature values.
To enable PGVector, set vector_enabled: true in the online store configuration.
The vector_length parameter can be used to specify the length of the vector in the Field.
Please make sure to follow the instructions in the repository, which, as the time of this writing, requires you to
run CREATE EXTENSION vector; in the database.
Then you can use retrieve_online_documents to retrieve the top k closest vectors to a query vector.
For the Retrieval Augmented Generation (RAG) use-case, you have to embed the query prior to passing the query vector.
{% code title="python" %}
from feast import FeatureStore from feast.infra.online_stores.postgres_online_store import retrieve_online_documents feature_store = FeatureStore(repo_path=".") query_vector = [0.1, 0.2, 0.3, 0.4, 0.5] top_k = 5 feature_values = retrieve_online_documents( feature_store=feature_store, feature_view_name="document_fv:embedding_float", query_vector=query_vector, top_k=top_k, )
{% endcode %}