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

• We welcome contribution to all items in the roadmap!

• Natural Language Processing

  • Vector Search (Alpha release. See RFC)
  • Enhanced Feature Server and SDK for native support for NLP

• Data Sources

  • Snowflake source
  • Redshift source
  • BigQuery source
  • Parquet file source
  • Azure Synapse + Azure SQL source (contrib plugin)
  • Hive (community plugin)
  • Postgres (contrib plugin)
  • Spark (contrib plugin)
  • Couchbase (contrib plugin)
  • Athena (contrib plugin)
  • Clickhouse (contrib plugin)
  • Oracle (contrib plugin)
  • Ray source (contrib plugin)
  • Kafka / Kinesis sources (via push support into the online store)

• Offline Stores

  • Snowflake
  • Redshift
  • BigQuery
  • DuckDB
  • Dask
  • Remote
  • Azure Synapse + Azure SQL (contrib plugin)
  • Hive (community plugin)
  • Postgres (contrib plugin)
  • Trino (contrib plugin)
  • Spark (contrib plugin)
  • Couchbase (contrib plugin)
  • Athena (contrib plugin)
  • Clickhouse (contrib plugin)
  • Ray (contrib plugin)
  • Oracle (contrib plugin)
  • Hybrid
  • Custom offline store support

• Online Stores

  • Snowflake
  • DynamoDB
  • Redis
  • Dragonfly
  • Datastore
  • Bigtable
  • SQLite
  • Remote
  • Postgres
  • HBase
  • Cassandra / AstraDB
  • ScyllaDB
  • MySQL
  • Hazelcast
  • Elasticsearch
  • SingleStore
  • Couchbase
  • MongoDB
  • Qdrant (vector store)
  • Milvus (vector store)
  • Faiss (vector store)
  • Hybrid
  • Azure Cache for Redis (community plugin)
  • Custom online store support

• Feature Engineering

  • On-demand Transformations (On Read) (Beta release. See RFC)
  • Streaming Transformations (Alpha release. See RFC)
  • Batch transformation (In progress. See RFC)
  • On-demand Transformations (On Write) (Beta release. See GitHub Issue)

• Streaming

  • Custom streaming ingestion job support
  • Push based streaming data ingestion to online store
  • Push based streaming data ingestion to offline store

• Deployments

  • AWS Lambda (Alpha release. See RFC)
  • Kubernetes (See guide)

• Feature Serving

  • Python Client
  • Python feature server
  • Feast Operator (alpha)
  • Java feature server (alpha)
  • Go feature server (alpha)
  • Offline Feature Server (alpha)
  • Registry server (alpha)

• Data Quality Management (See RFC)

  • Data profiling and validation (Great Expectations)

• Feature Discovery and Governance

  • Python SDK for browsing feature registry
  • CLI for browsing feature registry
  • Model-centric feature tracking (feature services)
  • Amundsen integration (see Feast extractor)
  • DataHub integration (see DataHub Feast docs)
  • Feast Web UI (Beta release. See docs)
  • Feast Lineage Explorer