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Hopsworks AI Lakehouse
hopsworks.ai
What it is
Hopsworks AI Lakehouse is a platform for building batch, real-time, and LLM AI systems using open standards. It supports Apache Iceberg, Delta Lake, and Apache Hudi, with streaming feature pipelines that feed 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, filter pushdown, credential vending, and reproducible training data. For LLM workflows, teams can query lakehouse data from prompts, integrate vector search for retrieval-augmented generation, and create fine-tuning instruction datasets while maintaining data governance. Feature, training, and inference pipelines cover batch, streaming, real-time, and LLM work, with trained models sent to a model registry. Integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases. Deployment options include SaaS, managed Kubernetes on 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; SaaS uses usage-based pricing, while Enterprise is custom-priced.
Spec sheet
- Purpose
- Hopsworks describes its AI Lakehouse as a platform for building batch, real-time, and LLM AI systems on open standards.Read 3 Oct 2026 · hopsworks.ai
- Intended users
- The documentation identifies developers, data scientists, platform engineers, security engineers, and administrators as user paths for the platform.Read 3 Oct 2026 · docs.hopsworks.ai
- Deployment
- The documentation describes managed SaaS and deployments on managed Kubernetes in AWS, Azure, or GCP, as well as air-gapped data centres.Read 3 Oct 2026 · docs.hopsworks.ai
- Integrations
- Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases.Read 3 Oct 2026 · hopsworks.ai
- 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.Read 3 Oct 2026 · hopsworks.ai
- Compliance
- The security page lists ISO 27001 and SOC 2 Type 2 certification and states that Hopsworks is GDPR compliant.Read 3 Oct 2026 · hopsworks.ai
- Support
- The Free and SaaS pricing tiers include community support, while Enterprise includes a dedicated support team and guaranteed SLA.Read 3 Oct 2026 · hopsworks.ai
- Headquarters
- Stockholm, SwedenRead 28 Sep 2026 · hopsworks.ai
- Founded
- 2017Read 28 Sep 2026 · hopsworks.ai
- 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.Read 3 Oct 2026 · hopsworks.ai
- Deployment requirements
- The Kubernetes installer page lists Kubernetes 1.27 or higher and recommends a minimum of 4–5 nodes.Read 3 Oct 2026 · hopsworks.ai
- 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.Read 3 Oct 2026 · hopsworks.ai
- 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.Read 3 Oct 2026 · hopsworks.ai
- Real-time features
- The product page says streaming feature pipelines connect to a low-latency serving database and provide sub-second feature freshness.Read 3 Oct 2026 · hopsworks.ai
- Table formats
- It natively supports Apache Iceberg, Delta Lake, and Apache Hudi.Read 3 Oct 2026 · hopsworks.ai
Plans and prices
Free Free 1 project · Feature Store + Model Registry · Community support · No credit card required Read 3 Oct 2026 · hopsworks.ai
Enterprise Priced on request Custom All SaaS features · On-premise & air-gapped · Dedicated support team · Custom integrations · SLA guaranteed Read 3 Oct 2026 · hopsworks.ai
SaaS Priced on request Pay as you go Unlimited projects · Feature Store + Model Registry · Model Serving · Usage-based pricing · Community support · Platform SLA Read 3 Oct 2026 · hopsworks.ai
Strong points and limits
Strong points
- Supports three open table formats.
- Sub-second feature freshness for streaming pipelines.
- Python query service supports reproducible training data.
- Free plan includes Feature Store and Model Registry.
- Offers SaaS, Kubernetes, and air-gapped deployment options.
Limits
- Free plan is limited to one project.
- Enterprise pricing is custom.
- Kubernetes installer recommends at least 4–5 nodes.
Who it suits
It suits developers, data scientists, platform engineers, security engineers, and administrators building AI systems around lakehouse data. The free plan offers a one-project starting point; larger deployments can use SaaS or Enterprise options.
Verdict
Hopsworks combines lakehouse storage, feature pipelines, model workflows, and LLM data use in one platform. The free tier is defined at free, while SaaS and Enterprise pricing are usage-based or custom rather than fixed.
Where Specifiction places it
- Model Registry Software#6 of 368.0
- ML Experiment Tracking Software#8 of 398.1
- Model registries#11 of 388.2
