Hopsworks
UnclaimedThe unified AI Lakehouse platform for real-time ML feature engineering, deployment, and production.
Visit WebsiteReviews onG2Capterra
5 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Achieves sub-millisecond latency for real-time feature retrieval and inference.
Biggest con
Requires Kubernetes knowledge for on-premises deployments using the K8s Installer.
TL;DR - Hopsworks
- Provides a unified AI Lakehouse for real-time ML, integrating feature engineering, MLOps, and model serving.
- Features a high-performance Feature Store with sub-millisecond latency powered by RonDB for consistent online/offline data.
- Supports open data formats (Iceberg, Delta, Hudi) and offers flexible deployment options including SaaS, on-premises, and air-gapped.
Pricing: Free plan available
Best for: Growing teams
4.5/5 across review platforms
What is Hopsworks?
Hopsworks is an AI Lakehouse platform designed to streamline the entire machine learning lifecycle, from feature engineering to model deployment and monitoring. It provides a unified environment for managing feature data, training models, and serving predictions with sub-millisecond latency. The platform is built for organizations looking to operationalize AI at scale, offering capabilities like a high-performance Feature Store powered by RonDB, direct integration with open data formats like Iceberg, Delta, and Hudi, and comprehensive MLOps tools.
It caters to data scientists, machine learning engineers, and data engineers who need to build, deploy, and run real-time AI systems. Key benefits include significant cost reduction through feature reuse, faster model deployment, and improved data consistency between training and production environments. Hopsworks supports various deployment options, including SaaS, on-premises, and air-gapped environments, ensuring data sovereignty and flexibility.
Available on: Web
Pros & Cons
Pros
- Achieves sub-millisecond latency for real-time feature retrieval and inference.
- Reduces costs and development time by enabling extensive feature reuse across models.
- Ensures data consistency between training and production environments, mitigating training-serving skew.
- Offers flexible deployment models including SaaS, on-premises, and air-gapped for data sovereignty.
- Integrates directly with open data formats like Iceberg, Delta, and Hudi without requiring data migrations.
Cons
- Requires Kubernetes knowledge for on-premises deployments using the K8s Installer.
- The full benefits of the platform are realized with a comprehensive understanding of ML engineering practices.
Ratings Across the Web
4.5(5 reviews)
Ratings aggregated from independent review platforms. Learn more
Key Features
Feature Store with sub-millisecond retrieval latency (powered by RonDB)AI Lakehouse supporting Iceberg, Delta, and Hudi tablesPython-native query engine for faster data readsMLOps Platform for experiment tracking, model registry, and deployment pipelinesGPU and compute management for LLMs and ML models (with Ray, KServe/vLLM support)Dual Storage System (Online RonDB for serving, Offline Hudi on HopsFS for training)Point-in-Time Correctness for generating historical training datasetsData Lineage and Feature Monitoring for audit trails and drift detection
Pricing Plans
Pricing checked Jun 11, 2026
Free
Free
- 1 project included
- Feature Store + Model Registry
- No credit card required
- Community support
- Upgrade anytime
SaaS
Pay as you go
- Unlimited projects
- Feature Store + Model Registry
- Model Serving
- Pay only for what you use
- Community support
- Platform SLA
Enterprise
Contact us
- All SaaS features
- On-premise & air-gapped
- Dedicated support team
- Custom integrations
- SLA guaranteed
Reviews
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4.5/5
Across 5 verified user reviews on Capterra, G2
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Hopsworks FAQ
How does Hopsworks support real-time machine learning applications?
Hopsworks achieves sub-millisecond latency for real-time feature retrieval and inference, making it suitable for demanding AI applications. It provides a high-performance Feature Store powered by RonDB to manage and serve feature data efficiently. This capability allows organizations to operationalize AI at scale with immediate prediction serving.
What kind of user benefits most from Hopsworks?
Hopsworks is designed for data scientists, machine learning engineers, and data engineers who need to build, deploy, and run real-time AI systems. It helps teams streamline the entire machine learning lifecycle, from feature engineering to model deployment and monitoring. The platform is particularly beneficial for organizations looking to operationalize AI at scale.
How does Hopsworks compare to Databricks for managing ML data?
Hopsworks focuses on providing a unified AI Lakehouse platform specifically for real-time ML feature engineering, deployment, and production. It offers capabilities like a high-performance Feature Store and sub-millisecond latency for feature retrieval. Databricks also provides a lakehouse platform, but Hopsworks emphasizes direct integration with open data formats like Iceberg, Delta, and Hudi without requiring data migrations.
Does Hopsworks integrate with open data formats?
Yes, Hopsworks integrates directly with open data formats such as Iceberg, Delta, and Hudi. This integration allows users to leverage existing data without requiring complex migrations. It ensures data consistency between training and production environments, mitigating training-serving skew.
What are the primary considerations for deploying Hopsworks on-premises?
Deploying Hopsworks on-premises using the Kubernetes Installer requires knowledge of Kubernetes. While it offers flexible deployment models including on-premises and air-gapped environments for data sovereignty, users should be prepared for the technical requirements of a Kubernetes-based setup. The full benefits of the platform are realized with a comprehensive understanding of ML engineering practices.
How is Hopsworks priced?
Hopsworks is available on a free tier, allowing users to get started with its core functionalities. For more extensive usage and advanced features, paid plans are offered. This tiered pricing model provides flexibility for different organizational needs and scales of operation.
Source: hopsworks.ai