Hopsworks AI Lakehouse vs Polyaxon
Hopsworks AI Lakehouse
hopsworks.aiPolyaxon
polyaxon.comSide by side
| Figure | Hopsworks AI Lakehouse | Polyaxon |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 1 |
| Spec score · Model Registry Software | 8.0 (#6) | 7.3 (#17) |
| Spec score · ML Experiment Tracking Software | 8.1 (#8) | 7.3 (#23) |
| Spec score · Model registries | 8.2 (#11) | 7.6 (#18) |
| Deployment | The documentation describes managed SaaS and deployments on managed Kubernetes in AWS, Azure, or GCP, as well as air-gapped data centres. | Polyaxon offers a managed cloud service and self-hosted deployments, including Community and Enterprise editions. |
| Integrations | Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases. | The site lists integrations including PyTorch, TensorFlow, Hugging Face, LangChain, Ray, Dask, Spark, AWS, GCP, Azure, GitHub, GitLab, Slack, and Datadog. |
| Purpose | Hopsworks describes its AI Lakehouse as a platform for building batch, real-time, and LLM AI systems on open standards. | Polyaxon is an AI engineering control plane for running machine learning, training, inference, and agent workloads on Kubernetes. |
| Support | The Free and SaaS pricing tiers include community support, while Enterprise includes a dedicated support team and guaranteed SLA. | For self-hosting issues, the setup guide directs users to troubleshooting, GitHub Discussions, or GitHub bug reports and feature requests. |
Plans
Hopsworks AI Lakehouse
- FreeFree
- EnterprisePriced on request
- SaaSPriced on request
In their own words
Hopsworks AI Lakehouse
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.
Polyaxon
Polyaxon is an AI engineering control plane for machine-learning training, inference and agent workloads on Kubernetes. It records run parameters, metrics, logs, code versions, artifacts, lineage and runtime state. Orchestration covers jobs, services, DAGs, schedules, sweeps, distributed workloads and reusable components. Isolated execution environments can be launched with controlled filesystems, network access, tools, SSH and runtime policies. Evaluation and monitoring include offline and online evaluations, logs, traces, metrics, health checks, alerts and dashboards. Listed integrations include PyTorch, TensorFlow, Hugging Face, LangChain, Ray, Dask, Spark, AWS, GCP, Azure, GitHub, GitLab, Slack and Datadog. Deployment is available through managed cloud or self-hosted Community and Enterprise editions. The core is Apache 2.0 licensed. A free Community Edition covers one cluster and namespace; paid access starts at $555/mo.