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  • Introduction
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    • Using Scalable Registry
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    • 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)
    • 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
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    • Offline stores
      • Overview
      • File
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    • Feature repository
      • feature_store.yaml
      • .feastignore
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      • Python feature server
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      • [Alpha] AWS Lambda feature server
    • [Beta] Web UI
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    • [Alpha] Vector Database
    • [Alpha] Data quality monitoring
    • Feast CLI reference
    • Python API reference
    • Usage
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    • 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

Offline stores

PreviousAzure Synapse + Azure SQL (contrib)NextOverview

Last updated 11 months ago

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Please see for a conceptual explanation of offline stores.

Offline Store
Overview
File
Snowflake
BigQuery
Redshift
DuckDB
Spark (contrib)
PostgreSQL (contrib)
Trino (contrib)
Azure Synapse + Azure SQL (contrib)