Feast alternatives

2 tools to consider instead of Feast, shown against it.

Feast Featureform Hopsworks
Vendor Linux Foundation AI & Data (Feast community) Redis (acquired Featureform, Inc., October 2025) Hopsworks AB
Pricing model Open source + paid options Quote only Usage-based
Free tier Yes — Yes
Deployment Self-hosted Cloud, Self-hosted Cloud, Self-hosted
Open source Yes (Apache-2.0) Yes (MPL-2.0) Yes (AGPL-3.0)
Best for ML teams needing a vendor-neutral, self-hosted registry to keep training and serving features consistent. Teams already on Redis (or evaluating it) who want a feature store without migrating existing pipelines. ML teams that want a feature store and model serving together, with a genuine self-hosted/on-prem option.
Pricing

Feast is free, open-source software with no vendor-hosted product or pricing page; you run and pay for your own infrastructure.

Pricing has not been verified yet — see the vendor's site.

No self-serve pricing is published; the product page offers a free trial, a demo, or a sales conversation, with no tiers or figures shown.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

A free single-project tier is available; SaaS is pay-as-you-go, and Enterprise (including on-prem) is custom-quoted.

Free $0
SaaS Pay-as-you-go
Enterprise Custom pricing

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Feature registry with versioned, code-defined feature definitions
  • Point-in-time-correct training dataset generation
  • Low-latency online feature serving (Redis, DynamoDB, and more)
  • Offline store support for major warehouses and lakes
  • Batch and streaming feature ingestion
  • Python SDK and feature server API
  • Vendor-neutral governance under the Linux Foundation
  • Feature definitions as code over existing data infrastructure
  • Unified batch and streaming feature pipelines
  • Sub-millisecond online serving via Redis
  • Feature versioning and lineage tracking
  • Multi-tenant workspace isolation
  • Role-based access control and audit logging
  • Orchestration across Snowflake, Databricks, Spark, and Postgres sources
  • Combined offline and online feature store with point-in-time joins
  • Built-in compute for feature pipelines (Spark, Python, Flink)
  • Model registry and model serving in the same platform
  • Vector search / embeddings support
  • Feature and model lineage
  • Self-hosted, SaaS, or air-gapped deployment options
  • Role-based access control and project isolation

In the index now