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SPECIFICTION
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Snowflake Feature Store

docs.snowflake.com

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Spec score 7.3 #23 of 38 in Model registries

What it is

Snowflake Feature Store lets data scientists and machine-learning engineers create, maintain, and use features inside Snowflake. It supports batch and streaming data with automatic updates, backfill, and point-in-time-correct features through ASOF JOIN. Transformations can be written in Python or SQL. Snowflake-managed feature views refresh incrementally on schedules, while external views are maintained by another process such as dbt. Integration with Snowflake Model Registry and user-managed dbt pipelines connects feature work with model workflows. ML Lineage traces data from source to feature, dataset, and trained model when the store is used. Snowsight provides feature search and discovery, and the Python API runs in a local IDE or Snowsight worksheet or notebook. Data stays under Snowflake governance with fine-grained role-based access control. The cloud service offers online and offline stores, monitoring, multi-region deployment, and up to 1024 dimensions. Pricing is consumption-based with no listed plan prices.

Spec sheet

Purpose
Snowflake Feature Store lets data scientists and ML engineers create, maintain, and use machine-learning features within Snowflake.Read 1 Oct 2026 · docs.snowflake.com
Integrations
The Feature Store integrates with Snowflake Model Registry and supports user-managed pipelines with dbt.Read 1 Oct 2026 · docs.snowflake.com
Security
Data remains under Snowflake governance and does not leave Snowflake, with access managed through fine-grained role-based access control.Read 1 Oct 2026 · docs.snowflake.com
Compliance
Snowflake lists global certifications and attestations including ISO 27001, ISO 27017, ISO 27018, SOC 1 Type II, and SOC 2 Type II.Read 1 Oct 2026 · docs.snowflake.com
Headquarters
Menlo Park, California, United StatesRead 28 Sep 2026 · docs.snowflake.com
Founded
2012Read 28 Sep 2026 · docs.snowflake.com
API platforms
The Snowflake Feature Store Python API is part of the snowflake-ml-python package and can be used in a local Python IDE or in a Snowsight worksheet or notebook.Read 1 Oct 2026 · docs.snowflake.com
Cost model
Snowflake-managed feature views use dynamic tables, while external feature views use views and incur no additional storage cost.Read 1 Oct 2026 · docs.snowflake.com
Data support
It supports batch and streaming data with automatic updates as new data arrives.Read 1 Oct 2026 · docs.snowflake.com
Examples and support
Snowflake quickstarts are examples only and are not guaranteed for accuracy or covered by a Snowflake Service Level Agreement.Read 1 Oct 2026 · docs.snowflake.com
Feature views
Snowflake-managed feature views refresh incrementally on a schedule, while external feature views are maintained by another process such as dbt.Read 1 Oct 2026 · docs.snowflake.com
Limits
Feature view versions have a maximum length of 128 characters, and Postgres-backed online serving limits combined feature-view name and version length to 46 characters.Read 1 Oct 2026 · docs.snowflake.com
Lineage
ML Lineage can trace data flow from source to feature to dataset to trained model and is automatically created when the Feature Store is used.Read 1 Oct 2026 · docs.snowflake.com
Point-in-time features
It supports backfill and point-in-time-correct features using ASOF JOIN.Read 1 Oct 2026 · docs.snowflake.com
Transformations
Feature transformations can be authored in Python or SQL.Read 1 Oct 2026 · docs.snowflake.com
User interface
Snowsight provides a Feature Store UI for searching and discovering features.Read 1 Oct 2026 · docs.snowflake.com

Plans and prices

Business Critical Priced on request consumption-based all Enterprise features · Tri-Secret Secure · private connectivity · failover and failback Read 1 Oct 2026 · snowflake.com
Enterprise Priced on request consumption-based all Standard features · multi-cluster compute · granular governance and privacy controls · extended Time Travel Read 1 Oct 2026 · snowflake.com
Standard Priced on request consumption-based core platform functionality · Snowpark · data sharing · optimized storage and Time Travel Read 1 Oct 2026 · snowflake.com
Virtual Private Snowflake Priced on request consumption-based all Business Critical features · completely separate isolated Snowflake environment Read 1 Oct 2026 · snowflake.com

Every Snowflake Feature Store plan and price →

Strong points and limits

Strong points

  • Batch and streaming feature updates
  • Point-in-time joins and backfill
  • Python and SQL transformations
  • Automatic ML lineage creation
  • Online and offline stores

Limits

  • Pricing is consumption-based with no listed prices
  • Feature-view versions max out at 128 characters
  • Postgres online names and versions max out at 46 characters
  • Quickstarts are not guaranteed or covered by an SLA

Who it suits

It suits data-science and machine-learning teams already working in Snowflake who need governed feature creation, lineage, and serving. Python, SQL, Snowsight, and dbt workflows are supported.

Verdict

Snowflake Feature Store centralizes feature engineering, lineage, governance, and serving within Snowflake. Teams should account for consumption billing and the documented naming-length limits.

Where Specifiction places it

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