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v0.35-branch
  • Introduction
  • Community & getting help
  • Roadmap
  • Changelog
  • Getting started
    • Quickstart
    • Concepts
      • Overview
      • Data ingestion
      • Entity
      • Feature view
      • Feature retrieval
      • Point-in-time joins
      • Registry
      • [Alpha] Saved dataset
    • Architecture
      • Overview
      • Registry
      • Offline store
      • Online store
      • Batch Materialization Engine
      • Provider
    • Third party integrations
    • FAQ
  • Tutorials
    • Sample use-case tutorials
      • 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
      • Scaling Feast
      • Structuring Feature Repos
    • Running Feast in production (e.g. on Kubernetes)
    • Upgrading for Feast 0.20+
    • Customizing Feast
      • Adding a custom batch materialization engine
      • Adding a new offline store
      • Adding a new online store
      • Adding a custom provider
    • Adding or reusing tests
  • Reference
    • Codebase Structure
    • Type System
    • Data sources
      • Overview
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Push
      • Kafka
      • Kinesis
      • Spark (contrib)
      • PostgreSQL (contrib)
      • Trino (contrib)
      • Azure Synapse + Azure SQL (contrib)
    • Offline stores
      • Overview
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Spark (contrib)
      • PostgreSQL (contrib)
      • Trino (contrib)
      • Azure Synapse + Azure SQL (contrib)
    • Online stores
      • Overview
      • SQLite
      • Snowflake
      • Redis
      • Dragonfly
      • Datastore
      • DynamoDB
      • Bigtable
      • PostgreSQL (contrib)
      • Cassandra + Astra DB (contrib)
      • MySQL (contrib)
      • Rockset (contrib)
      • Hazelcast (contrib)
    • Providers
      • Local
      • Google Cloud Platform
      • Amazon Web Services
      • Azure
    • Batch Materialization Engines
      • Bytewax
      • Snowflake
      • AWS Lambda (alpha)
      • Spark (contrib)
    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feature servers
      • Python feature server
      • [Alpha] Go feature server
      • [Alpha] AWS Lambda feature server
    • [Beta] Web UI
    • [Alpha] On demand feature view
    • [Alpha] Data quality monitoring
    • Feast CLI reference
    • Python API reference
    • Usage
  • Project
    • Contribution process
    • Development guide
    • Backwards Compatibility Policy
      • Maintainer Docs
    • Versioning policy
    • Release process
    • Feast 0.9 vs Feast 0.10+
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  1. Reference

Batch Materialization Engines

PreviousAzureNextBytewax

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Please see for an explanation of batch materialization engines.

Batch Materialization Engine
Snowflake
Bytewax
AWS Lambda (alpha)
Spark (contrib)