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# Redis Feature Form

A feature store made to get ML features into prod—fast.

Machine learning thrives on real-time data, but creating real-time pipelines can seem impossible. Not with Feature Form. Simply define your features as code, and Feature Form will turn them into prod-grade data pipelines for model training and inference.

[Schedule a demo](/content/meeting/index.html) [Read the docs](/content/docs/latest/develop/ai/featureform/index.html)

- [How it works](/content/feature-form/#howitworks/index.html)
- [Customers](/content/feature-form/#customers/index.html)
- [Key features](/content/feature-form/#keyfeatures/index.html)
- [Get started](/content/feature-form/#getstarted/index.html)

## Operationalize real-time data for machine learning

Feature Form orchestrates between your offline data systems and real-time serving. It turns your feature definitions into computation across Snowflake, Databricks, and more, and keeps your Redis online store up to date for low-latency feature retrieval.

- Real-time feature pipelines made easy
- Works on your existing data stack
- Define features once and use them for training and inference

[Read our blog](/content/blog/introducing-redis-feature-form/index.html)

## Built for enterprise AI teams

Keep teams from reinventing features, understand which models are using which features, and learn how features are evolving over time.

- Workspace-scoped auth and permissions
- Isolated data providers and configs
- Independent observability per workspace

[Explore our docs](/content/docs/latest/develop/ai/featureform/index.html)

## Get finely-tuned feature control

Plan and validate changes before they hit production with full visibility into how updates affect downstream pipelines and models.

- Plan changes with ff apply --plan
- Run impact analyses across pipelines
- Split materializations into discrete jobs
- Trace execution with OpenTelemetry

[Learn how it works](/content/docs/latest/operate/featureform/index.html)

## Keep data secure at any scale

Maintain full access control, auditability, and stay compliant without compromising speed. Security is part of the system.

- Workspace-scoped RBAC
- API key pairs and model roles
- Audit logs for every change
- Secret providers, mTLS, encrypted transport

[Explore data security](/content/docs/latest/operate/featureform/auth/index.html)

<1ms millisecond per read

38% decrease in latency

"It’s not just about putting in a food order. It’s about providing an optimal experience for our customers. It’s really, really fast. Plus it’s a lot cheaper.  
Daniel Galinkin, Head of ML Engineering"

"We also saw a 38% decrease in Redis latencies, helping to improve the runtime performance of serving models.  
Arbaz Khan, Staff Software Engineer"

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## Redis Feature Form

Workspaces & multi-tenancy

Run multiple ML teams on one platform with workspace isolation, scoped access, and independent environments.

[See how it works](/content/docs/latest/develop/ai/featureform/streaming/index.html)

Atomic DAGs & version control

Plan, apply, and roll back changes at the graph level so updates are consistent, traceable, and never partially applied. Scale with Apache Iceberg for indexing, time travel, and high-performance access to large datasets.

[Learn more](/content/docs/latest/develop/ai/featureform/training-sets-and-feature-views/index.html)

One platform, full feature lifecycles

Define features once, orchestrate pipelines across your data stack, and serve in real time—without stitching together scripts and systems.

[Read the docs](/content/docs/latest/develop/ai/featureform/providers/index.html)

Learn about tracking

Ensure models see the same feature definitions in training and production, eliminating drift and preventing silent failures

[See how tracking works](/content/docs/latest/develop/ai/featureform/features-and-labels/index.html)

## Redis as an online store

Open architecture, no lock-in

Integrate with Snowflake, Databricks, Spark, Postgres, and more while Redis handles real-time serving. Use Feast as your offline feature store and Redis for real-time online serving.

[See how it works](https://www.youtube.com/watch?v=dvPp7OGkEQw)

Sub-ms feature serving

Serve features instantly at scale for fraud detection, recommendations, real-time decisioning, and more.

[Watch a demo](https://www.youtube.com/watch?v=kQKfXi7NfWs)

Built for high availability

Built-in replication and failover keep features available when your models need them.

[Learn how it works](/content/blog/feature-stores-for-real-time-artificial-intelligence-and-machine-learning/index.html)

Keep features fresh in real time

Continuously update feature values so models always use the latest data.

[Read about updates](/content/blog/building-feature-stores-with-redis-introduction-to-feast-with-redis/index.html)

## Get started

Meet with a Redis expert and build your feature store today.

[Start for free](/content/try-free/index.html) [Talk to sales](/content/meeting/index.html)