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  • Introduction
  • Community
  • Roadmap
  • Changelog
  • Getting started
    • Quickstart
    • Concepts
      • Overview
      • Data source
      • Dataset
      • Entity
      • Feature view
      • Stream feature view
      • Feature retrieval
      • Point-in-time joins
      • Registry
    • Architecture
      • Overview
      • Feature repository
      • Registry
      • Offline store
      • Online store
      • Provider
    • Learning by example
    • Third party integrations
    • FAQ
  • Tutorials
    • Overview
    • Driver ranking
    • Fraud detection on GCP
    • Real-time credit scoring on AWS
    • Driver stats on Snowflake
    • Validating historical features with Great Expectations
    • Using Scalable Registry
    • Building streaming features
  • How-to Guides
    • Running Feast with Snowflake/GCP/AWS
      • Install Feast
      • Create a feature repository
      • Deploy a feature store
      • Build a training dataset
      • Load data into the online store
      • Read features from the online store
    • Running Feast in production
    • Deploying a Java feature server on Kubernetes
    • Upgrading from Feast 0.9
    • Adding a custom provider
    • Adding a new online store
    • Adding a new offline store
    • Adding or reusing tests
  • Reference
    • Codebase Structure
    • Data sources
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Push
      • Kafka
      • Kinesis
      • Spark (contrib)
      • PostgreSQL (contrib)
    • Offline stores
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Spark (contrib)
      • PostgreSQL (contrib)
    • Online stores
      • SQLite
      • Redis
      • Datastore
      • DynamoDB
      • PostgreSQL (contrib)
    • Providers
      • Local
      • Google Cloud Platform
      • Amazon Web Services
    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feature servers
      • Python feature server
      • Go-based feature retrieval
    • [Alpha] Web UI
    • [Alpha] Data quality monitoring
    • [Alpha] On demand feature view
    • [Alpha] AWS Lambda feature server
    • Feast CLI reference
    • Python API reference
    • Usage
  • Project
    • Contribution process
    • Development guide
    • Versioning policy
    • Release process
    • Feast 0.9 vs Feast 0.10+
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Roadmap

PreviousCommunityNextQuickstart

Last updated 2 years ago

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The list below contains the functionality that contributors are planning to develop for Feast

  • Items below that are in development (or planned for development) will be indicated in parentheses.

  • We welcome contribution to all items in the roadmap!

  • Have questions about the roadmap? Go to the Slack channel to ask on #feast-development

  • Data Sources

  • Offline Stores

  • Online Stores

  • Feature Engineering

  • Streaming

  • Deployments

  • Feature Serving

  • Data Quality Management (See )

  • Feature Discovery and Governance

Snowflake source
Redshift source
BigQuery source
Parquet file source
Synapse source (community plugin)
Hive (community plugin)
Postgres (contrib plugin)
Spark (contrib plugin)
push support into the online store
Snowflake
Redshift
BigQuery
Synapse (community plugin)
Hive (community plugin)
Postgres (contrib plugin)
Trino (contrib plugin)
Spark (contrib plugin)
In-memory / Pandas
Custom offline store support
DynamoDB
Redis
Datastore
SQLite
Azure Cache for Redis (community plugin)
Postgres (contrib plugin)
Custom online store support
Cassandra / AstraDB
RFC
RFC
RFC
Custom streaming ingestion job support
Push based streaming data ingestion to online store (Alpha)
Push based streaming data ingestion to offline store (Alpha)
RFC
guide
RFC
docs
#1497
RFC
Feast extractor
DataHub Feast docs
documentation