docs/reference/online-stores/postgres.md
The PostgreSQL online store provides support for materializing feature values into a PostgreSQL database for serving online features.
Only the latest feature values are persisted
sslmode defaults to require, which encrypts the connection without certificate verification. To disable SSL (e.g. for local development), set sslmode: disable. For certificate verification, set sslmode to verify-ca or verify-full and provide the corresponding sslrootcert_path (and optionally sslcert_path and sslkey_path for mutual TLS)
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.
{% 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.
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.
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 %}