Here’s the difference between Lightdash and Onehouse. The comparison is based on pricing, deployment, business model, and other important factors.
Lightdash removes the gap between your data transformation layer and your data visualization layer. It enables data analysts and engineers to control all of their business intelligence (data transformations/business logic as well as data visualization) in a single place. Lightdash integrates with your dbt project and gives a framework for defining metrics and specifying joins between models all within your existing dbt YAML files. The data output from your dbt project is then available for exploring and sharing in Lightdash.
Onehouse delivers a new bedrock for your data, through a cloud-native managed lakehouse service built on Apache Hudi, which was created by the founding team while they were at Uber. Onehouse makes it possible to blend the ease of use of a warehouse with the scale of a data lake, by offering a seamless experience for engineers to get their data lakes up and running.
|Categories||Metrics Store, Business Intelligence (BI)||Data Lakes|
|Stage||Early Stage||Early Stage|
|Target Segment||Mid size, SMBs||SMBs, Mid-size, Enterprise|
|Deployment||Open source||Open source|
|Business Model||Open Source||Commercial|
|Location||UK||Menlo Park, California|
|Companies using it|