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!

• Want to speak to a Feast contributor? We are more than happy to jump on a call. Please schedule a time using Calendly.

• Data Sources

  • Snowflake source
  • Redshift source
  • BigQuery source
  • Parquet file source
  • Synapse source (community plugin)
  • Hive (community plugin)
  • Postgres (contrib plugin)
  • Spark (contrib plugin)
  • Kafka / Kinesis sources (via push support into the online store)
  • HTTP source

• Offline Stores

  • 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

• Online Stores

  • DynamoDB
  • Redis
  • Datastore
  • SQLite
  • Azure Cache for Redis (community plugin)
  • Postgres (contrib plugin)
  • Custom online store support
  • Cassandra / AstraDB
  • Bigtable (in progress)

• Feature Engineering

  • On-demand Transformations (Alpha release. See RFC)
  • Streaming Transformations (Alpha release. See RFC)
  • Batch transformation (In progress. See RFC)

• Streaming

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

• Deployments

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

• Feature Serving

  • Python Client
  • REST Feature Server (Python) (Alpha release. See RFC)
  • gRPC Feature Server (Java) (See #1497)
  • Push API
  • Java Client
  • Go Client
  • Delete API
  • Feature Logging (for training)

• Data Quality Management (See RFC)

  • Data profiling and validation (Great Expectations)
  • Training-serving skew detection (in progress)
  • Metric production
  • Drift detection

• 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)
  • Feast Web UI (Alpha release. See documentation)
  • REST API for browsing feature registry