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Tech riderRev. 4 Oct 2026

Agent Platform Feature Store

Ch 116.3of 17 Feature Store Software
  1. 1Runs onAPI, Web
  2. 2CostsNot stated by the maker
  3. 3Online storeYes
  4. 4Offline storeYes
  5. 5Point-in-time joinsYes
  6. 6Feature monitoringYes
  7. 7Deployment modelcloud
  8. 8Serving modesboth
7 lines stated Written from the maker's own pages: cloud.google.com
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Overview

Agent Platform Feature Store is ranked #11 of 17 in feature store software on Specifiction. It runs on API, Web. There is no free plan.

Agent Platform Feature Store plans and pricing

All plans
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
Nocloud.google.com
Online store
Yescloud.google.com
Offline store
Yescloud.google.com
Point-in-time joins
Yescloud.google.com
Feature monitoring
Yescloud.google.com
Deployment model
cloudcloud.google.com
Serving modes
bothcloud.google.com

Facts

Purpose
It is a managed, cloud-native feature store for managing ML features and serving them online from BigQuery data sources.docs.cloud.google.com · 4 Oct 2026
Offline data
BigQuery tables and views form the offline store, so Feature Store does not provision a separate offline store.docs.cloud.google.com · 4 Oct 2026
Online predictions
It serves the latest feature values from BigQuery for online predictions at low latencies.docs.cloud.google.com · 4 Oct 2026
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.docs.cloud.google.com · 4 Oct 2026
Monitoring
Feature monitoring can run on a schedule or manually to retrieve statistics and detect anomalies such as feature drift.docs.cloud.google.com · 4 Oct 2026
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.docs.cloud.google.com · 4 Oct 2026
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.docs.cloud.google.com · 4 Oct 2026
Embeddings
Google recommends its purpose-built Vector Search to efficiently store and serve embeddings.docs.cloud.google.com · 4 Oct 2026
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.docs.cloud.google.com · 4 Oct 2026
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.docs.cloud.google.com · 4 Oct 2026
Data retention
The online store has no data retention limit, while BigQuery retention limits or quotas may apply to the offline data.docs.cloud.google.com · 4 Oct 2026
Support and learning
The documentation links to Google Cloud Support, community forums, release notes, and tutorials with Colab and GitHub examples.docs.cloud.google.com · 4 Oct 2026

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Where it ranks on Specifiction

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