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Guild AI vs Hopsworks AI Lakehouse

Guild AI

guildai.org

Hopsworks AI Lakehouse

hopsworks.ai

Side by side

FigureGuild AIHopsworks AI Lakehouse
Price from—Free
Free plan—Yes
Free trial——
Open source——
WebYesYes
WindowsYes—
macOSYes—
LinuxYesYes
API—Yes
Self-hosted—Yes
Plans published03
Spec score · ML Experiment Tracking Software7.6 (#14)8.1 (#8)
IntegrationsThe documentation describes TensorBoard support and integrations involving TensorFlow and Keras.Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, AWS SageMaker, Spark, Vertex AI, and Weights & Biases.
PurposeGuild AI is an open-source toolkit for automating and optimizing machine learning experiments.Hopsworks describes its AI Lakehouse as a platform for building batch, real-time, and LLM AI systems on open standards.
SupportThe Guild AI forum says its support systems are moving to GitHub and that the forum will be read-only.The Free and SaaS pricing tiers include community support, while Enterprise includes a dedicated support team and guaranteed SLA.

Plans

Guild AI

No plans published.

Guild AI pricing →

Hopsworks AI Lakehouse

  • FreeFree
  • EnterprisePriced on request
  • SaaSPriced on request

Hopsworks AI Lakehouse pricing →

In their own words

Guild AI

Guild AI has no write-up on Specifiction yet; its figures are above.

Visit guildai.org

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.

Visit hopsworks.ai