Hopsworks AI Lakehouse

Hopsworks AI Lakehouse is ranked #8 of 37 in ML experiment tracking software on The Geeks Club. It runs on API, Linux, Self-hosted, Web. There is a free plan.

Hopsworks AI Lakehouse plans and pricing

All plans

Free Free 1 project · Feature Store + Model Registry · Community support · No credit card required hopsworks.ai · 3 Oct 2026

SaaS Not published Pay as you go Unlimited projects · Feature Store + Model Registry · Model Serving · Usage-based pricing · Community support · Platform SLA hopsworks.ai · 3 Oct 2026

Enterprise Not published Custom All SaaS features · On-premise & air-gapped · Dedicated support team · Custom integrations · SLA guaranteed hopsworks.ai · 3 Oct 2026

Compared on ML experiment tracking software

Free plan: Yes
Run comparison: Yes
Artifact tracking: Yes
Dataset versioning: Yes
Model registry: Yes
API and SDK access: Yes

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Hopsworks AI Lakehouse

Purpose: Hopsworks describes its AI Lakehouse as a platform for building batch, real-time, and LLM AI systems on open standards.
Table formats: It natively supports Apache Iceberg, Delta Lake, and Apache Hudi.
Real-time features: The product page says streaming feature pipelines connect to a low-latency serving database and provide sub-second feature freshness.
Python query service: Hopsworks Query Service uses Arrow-native transfer to Python clients and supports temporal joins, pushdown filters, credential vending, and reproducible training data creation.
LLM workflows: The platform supports querying Lakehouse data from LLM prompts, vector search integration for RAG, and instruction dataset creation for fine-tuning while maintaining data governance.
AI pipelines: Its feature, training, and inference pipelines support batch, streaming, real-time, and LLM AI workflows, with trained models output to a model registry.
Integrations: Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases.
Deployment: The documentation describes managed SaaS and deployments on managed Kubernetes in AWS, Azure, or GCP, as well as air-gapped data centres.
Security: Hopsworks says it encrypts data at rest and in transit and provides project-based access controls, audit logs, and authentication options including 2FA and SSO.
Compliance: The security page lists ISO 27001 and SOC 2 Type 2 certification and states that Hopsworks is GDPR compliant.
Support: The Free and SaaS pricing tiers include community support, while Enterprise includes a dedicated support team and guaranteed SLA.
Deployment requirements: The Kubernetes installer page lists Kubernetes 1.27 or higher and recommends a minimum of 4–5 nodes.
Intended users: The documentation identifies developers, data scientists, platform engineers, security engineers, and administrators as user paths for the platform.
Founded: 2017
Price from: Free

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Where it ranks on The Geeks Club

Best ML Experiment Tracking Software in 2026#8 of 37
Best Model Registry Software in 2026#7 of 33

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Sources

hopsworks.ai/product-capabilities/ai-lakehouse· checked 3 Oct 2026
hopsworks.ai/integrations· checked 3 Oct 2026
docs.hopsworks.ai/latest/· checked 3 Oct 2026
hopsworks.ai/security-compliance· checked 3 Oct 2026
hopsworks.ai/pricing· checked 3 Oct 2026