Hopsworks vs Feast

Side-by-side — pricing, strengths, tradeoffs, and fit.

Hopsworks

Open-source feature store for AI applications with both offline and online serving capabilities.

Feast

Feature store for ML features management and access.

At a glance

Open SourceFree Tier
◌ Declining·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

Open-source feature store for AI applications with both offline and online serving capabilities.

One-liner

Feature store for ML features management and access.

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Organizations needing a self-hosted, open-source solution for feature management in both offline and online contexts.
Teams that require integration with Apache Hive for batch processing and MySQL Cluster for real-time serving.

✓ Best for

Teams needing a unified system for managing ML features across different stages of the model lifecycle
Projects that require real-time feature retrieval in production environments
Organizations looking to ensure consistency between training and serving datasets

Not ideal for

✕ Not for

Projects requiring cloud-based managed services without the need to manage their own infrastructure
Applications needing a more lightweight or simpler setup than what Hopsworks offers

✕ Not for

Small projects or startups without significant data infrastructure needs
Teams preferring a fully managed service over self-hosted solutions

Strengths

↑ Strengths

Offline feature warehouse based on Apache Hive
Online feature serving database using MySQL Cluster
Support for both batch and real-time data processing
Open-source with AGPL-3.0 license

↑ Strengths

Unified access to features for both training and serving
Supports real-time feature retrieval
Integration with popular data sources like BigQuery, Snowflake, and Redis

Weaknesses

↓ Weaknesses

Steep learning curve for non-Java developers
Limited documentation and community support
Performance issues with large-scale data processing
Complex setup and configuration

↓ Weaknesses

Limited support for data sources beyond the popular ones mentioned
Complex setup and configuration process
Full Hopsworks profile →Full Feast profile →