Agent Platform Feature Store

Agent Platform Feature Store is ranked #15 of 17 in feature store software on The Geeks Club. It runs on API, Web. There is no free plan.

Agent Platform Feature Store plans and pricing

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New Agent Platform Feature Store (pay-as-you-go) Not published Usage-based; online operations are charged per node-hour, to the minute. Offline operations use BigQuery pricing. Data processing node: $0.08 / 1 hour · Optimized online serving node: $0.30 / 1 hour · Bigtable online serving node: $0.94 / 1 hour · Bigtable online serving storage: $0.000342466 / 1 gibibyte hour · Offline operations: BigQuery pricing cloud.google.com · 4 Oct 2026

Compared on feature store software

Free plan: No
Online store: Yes
Offline store: Yes
Point-in-time joins: Yes
Feature monitoring: Yes
Deployment model: cloud
Serving modes: both

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Agent Platform Feature Store

Purpose: It is a managed, cloud-native feature store for managing ML features and serving them online from BigQuery data sources.
Offline data: BigQuery tables and views form the offline store, so Feature Store does not provision a separate offline store.
Online predictions: It serves the latest feature values from BigQuery for online predictions at low latencies.
Feature registry: Registering data sources and feature columns in the Feature Registry is optional; registration supports selecting columns, combining sources, and monitoring statistics and drift.
Monitoring: Feature monitoring can run on a schedule or manually to retrieve statistics and detect anomalies such as feature drift.
Serving options: Bigtable online serving supports large data volumes but not embeddings; optimized online serving is deprecated and scheduled to sunset on February 17, 2027.
Data sync limit: Optimized online serving supports scheduled data sync but not continuous data sync; Bigtable online serving supports near-real-time continuous sync from BigQuery.
Embeddings: Google recommends its purpose-built Vector Search to efficiently store and serve embeddings.
IAM access control: IAM policies can control access to feature groups, online store instances, and feature views, with bindings for users, groups, domains, and service accounts.
Location constraint: Feature Store resources must be in the same region or multi-region as the BigQuery source, and dual-region bucket sources are unsupported.
Data retention: The online store has no data retention limit, while BigQuery retention limits or quotas may apply to the offline data.
Support and learning: The documentation links to Google Cloud Support, community forums, release notes, and tutorials with Colab and GitHub examples.

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Where it ranks on The Geeks Club

Best Feature Store Software in 2026#15 of 17

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Sources

docs.cloud.google.com/gemini-enterprise-agent-platform/machin· checked 4 Oct 2026
docs.cloud.google.com/gemini-enterprise-agent-platform/machin· checked 4 Oct 2026
docs.cloud.google.com/gemini-enterprise-agent-platform/machin· checked 4 Oct 2026
cloud.google.com/products/gemini-enterprise-agent-platfo· checked 4 Oct 2026