Hopsworks AI Lakehouse
Ranked in ML Experiment Tracking Software·Free plan
About
Hopsworks AI Lakehouse is a platform for building batch, real-time and LLM AI systems using open standards. It natively supports Apache Iceberg, Delta Lake and Apache Hudi. Streaming feature pipelines connect to a low-latency serving database and provide sub-second feature freshness. Its Query Service transfers data to Python clients using Arrow and supports temporal joins, pushdown filters, credential vending and reproducible training data creation. LLM workflows can query Lakehouse data from prompts, integrate vector search for retrieval-augmented generation and create instruction datasets for fine-tuning while retaining data governance. Feature, training and inference pipelines span batch, streaming, real-time and LLM workloads, with trained models output to a model registry. Integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI and Weights & Biases. Deployment options range from managed SaaS to managed Kubernetes in AWS, Azure or GCP and air-gapped data centres. The Free plan is free and includes one project, Feature Store, Model Registry and community support.
Who it is for
The platform suits developers, data scientists, platform engineers, security engineers and administrators building AI workflows around lakehouse data. Teams can choose SaaS, managed Kubernetes or air-gapped deployment, depending on their environment.
What is good
- Supports Apache Iceberg, Delta Lake and Apache Hudi.
- Feature pipelines provide sub-second freshness.
- Query Service offers Arrow transfer to Python clients.
- Free plan includes one project and community support.
- Lists ISO 27001 and SOC 2 Type 2 certifications.
What to know first
- Free plan is limited to one project.
- Free and SaaS tiers include community support.
- Kubernetes installer requires version 1.27 or higher.
- Installer recommends at least four to five nodes.
Verdict
Hopsworks brings lakehouse storage, feature pipelines, model workflows and LLM use cases together, with multiple deployment options. The free plan is narrow at one project, while Kubernetes deployments have stated version and node requirements.
Compared on ML experiment tracking software
- Free plan
- Yeshopsworks.ai
- Run comparison
- Yeshopsworks.ai
- Artifact tracking
- Yeshopsworks.ai
- Dataset versioning
- Yeshopsworks.ai
- Model registry
- Yeshopsworks.ai
- API and SDK access
- Yeshopsworks.ai
Facts
- Purpose
- Hopsworks describes its AI Lakehouse as a platform for building batch, real-time, and LLM AI systems on open standards.hopsworks.ai · 3 Oct 2026
- Table formats
- It natively supports Apache Iceberg, Delta Lake, and Apache Hudi.hopsworks.ai · 3 Oct 2026
- Real-time features
- The product page says streaming feature pipelines connect to a low-latency serving database and provide sub-second feature freshness.hopsworks.ai · 3 Oct 2026
- 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.hopsworks.ai · 3 Oct 2026
- 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.hopsworks.ai · 3 Oct 2026
- 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.hopsworks.ai · 3 Oct 2026
- Integrations
- Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases.hopsworks.ai · 3 Oct 2026
- Deployment
- The documentation describes managed SaaS and deployments on managed Kubernetes in AWS, Azure, or GCP, as well as air-gapped data centres.docs.hopsworks.ai · 3 Oct 2026
- 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.hopsworks.ai · 3 Oct 2026
- Compliance
- The security page lists ISO 27001 and SOC 2 Type 2 certification and states that Hopsworks is GDPR compliant.hopsworks.ai · 3 Oct 2026
- Support
- The Free and SaaS pricing tiers include community support, while Enterprise includes a dedicated support team and guaranteed SLA.hopsworks.ai · 3 Oct 2026
- Deployment requirements
- The Kubernetes installer page lists Kubernetes 1.27 or higher and recommends a minimum of 4–5 nodes.hopsworks.ai · 3 Oct 2026
- Intended users
- The documentation identifies developers, data scientists, platform engineers, security engineers, and administrators as user paths for the platform.docs.hopsworks.ai · 3 Oct 2026
Company
- Founded
- 2017hopsworks.ai · 28 Sept 2026
- Headquarters
- Stockholm, Swedenhopsworks.ai · 28 Sept 2026
Best Hopsworks AI Lakehouse alternatives
See all 20
Where it ranks on Inferse
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