{
  "schema_version": 2,
  "id": "develop/ai/featureform",
  "title": "Redis Feature Form",
  "url": "https://redis.io/docs/latest/develop/ai/featureform/",
  "summary": "Build feature engineering workflows with Redis Feature Form.",
  "tags": [
    "docs",
    "develop",
    "ai"
  ],
  "last_updated": "2026-09-24T18:15:36-07:00",
  "children": [
    {
      "id": "develop/ai/featureform/overview",
      "summary": "Learn what Redis Feature Form is, who it is for, and how it fits into Redis-based ML workflows.",
      "title": "Redis Feature Form overview",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/overview/"
    },
    {
      "id": "develop/ai/featureform/manage-workspace",
      "summary": "Create, verify access to, monitor, and delete Redis Feature Form workspaces with the ff CLI.",
      "title": "Manage workspaces",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/manage-workspace/"
    },
    {
      "id": "develop/ai/featureform/quickstart",
      "summary": "Register providers, define a feature, materialize it to Redis, and serve it.",
      "title": "Redis Feature Form quickstart",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/quickstart/"
    },
    {
      "id": "develop/ai/featureform/concepts",
      "summary": "Learn the workspace, resource graph, provider, secret, and serving model behind Redis Feature Form.",
      "title": "Redis Feature Form concepts",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/concepts/"
    },
    {
      "id": "develop/ai/featureform/register-providers",
      "summary": "Register storage, compute, catalog, and secret providers in a Redis Feature Form workspace.",
      "title": "Register providers",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/register-providers/"
    },
    {
      "id": "develop/ai/featureform/define-and-deploy-features",
      "summary": "Author a Python definitions file and apply it to a Redis Feature Form workspace.",
      "title": "Define and deploy features",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/define-and-deploy-features/"
    },
    {
      "id": "develop/ai/featureform/update-features",
      "summary": "Iterate on a Redis Feature Form definitions file with plan, merge, and re-apply workflows.",
      "title": "Update features",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/update-features/"
    },
    {
      "id": "develop/ai/featureform/serve-features",
      "summary": "Read materialized features from a Redis Feature Form feature view at inference time.",
      "title": "Serve features",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/serve-features/"
    },
    {
      "id": "develop/ai/featureform/query-data",
      "summary": "Inspect the Redis Feature Form catalog and query datasets, training sets, and feature views with the ff CLI.",
      "title": "Query data",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/query-data/"
    },
    {
      "id": "develop/ai/featureform/reference",
      "summary": "Reference data for the ff CLI, Python client, gRPC API, and RBAC permissions.",
      "title": "Redis Feature Form reference",
      "url": "https://redis.io/docs/latest/develop/ai/featureform/reference/"
    }
  ],
  "page_type": "content",
  "content_hash": "5b8fb5a51fdb75d25adb6ee0a30673510f5abfb781e530a4ca989929cba77d21",
  "sections": [
    {
      "id": "overview",
      "title": "Overview",
      "role": "overview",
      "text": "Define, manage, and serve machine learning features on top of your existing data systems, without replacing them.\n\nRedis Feature Form lets you register your data providers, define features as Python transformations, materialize them on a schedule, and serve them at low latency from Redis. Your existing databases stay in place; Feature Form coordinates the pipeline.\n\n<div class=\"grid grid-cols-1 md:grid-cols-3 gap-6 my-8\">\n  \n  \n  \n</div>"
    },
    {
      "id": "what-is-redis-feature-form",
      "title": "What is Redis Feature Form?",
      "role": "content",
      "text": "Redis Feature Form is a feature platform for machine learning teams that:\n\n- **Works with your existing data**: Register your databases, data warehouses, and streams as providers; no migration required\n- **Defines features as code**: Write transformations in Python and version them alongside your model code\n- **Materializes on demand**: Push computed features to Redis for sub-millisecond online serving\n- **Serves training and inference from the same definitions**: Training sets and online feature views share one source of truth\n- **Supports streaming features**: Ingest real-time events and serve up-to-the-second feature values"
    },
    {
      "id": "why-use-redis-feature-form",
      "title": "Why use Redis Feature Form?",
      "role": "content",
      "text": "<div class=\"grid grid-cols-1 md:grid-cols-2 gap-6 my-6\">\n  <div class=\"p-5 border border-redis-pen-300 rounded-lg\">\n    <h3 class=\"text-redis-ink-900 font-semibold mb-3\">For ML teams</h3>\n    <ul class=\"space-y-1 text-redis-pen-600\">\n      <li>Consistent features between training and serving: no training-serving skew</li>\n      <li>Version and audit feature definitions alongside model code</li>\n      <li>Reuse features across multiple models and teams</li>\n      <li>Streaming support for time-sensitive predictions</li>\n    </ul>\n  </div>\n  <div class=\"p-5 border border-redis-pen-300 rounded-lg\">\n    <h3 class=\"text-redis-ink-900 font-semibold mb-3\">For developers</h3>\n    <ul class=\"space-y-1 text-redis-pen-600\">\n      <li>Python SDK for defining features, labels, training sets, and providers</li>\n      <li>Redis as the online store: sub-millisecond feature serving at scale</li>\n      <li>No need to replace existing data systems: register them as providers</li>\n    </ul>\n  </div>\n</div>\n\nRedis Feature Form helps teams define, manage, materialize, and serve machine learning features while keeping existing data systems in place. In the documented workflow, Redis acts as the low-latency online store for feature serving.\n\nThis documentation describes platform setup, workspace access, provider and secret registration, definitions-file authoring, apply, and serving. Refer to [Deploy](https://redis.io/docs/latest/operate/featureform) for installation and authentication instructions."
    }
  ],
  "examples": []
}