Compare - Count VS Onehouse
Here’s the difference between Count and Onehouse. The comparison is based on pricing, deployment, business model, and other important factors.
About Count
Count is a collaborative data whiteboard. It combines all the power of your SQL IDE, Python notebook, and BI tool - in a reactive, real-time canvas. Instead of working one query at a time in an IDE, the canvas lets you lay out your entire thought process in one place, and explain not just the answer but how you got there. Analyze data with SQL, Python, or drag-and-drop query builders. Import and export dbt models. Run queries against your database, or locally in the browser using DuckDB and Python. Share canvases to get help from a teammate or feedback from stakeholders. Turn any canvas into a dashboard, report, interactive app, or even a slide deck.
About Onehouse
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.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Workspace/ Collaboration | Data Lakes |
| Stage | Mid Stage | Early Stage |
| Target Segment | Mid Size, Enterprise | SMBs, Mid-size, Enterprise |
| Deployment | SaaS | Open source |
| Business Model | Commercial | Commercial |
| Pricing | Freemium, Contact Sales | Conatct Sales |
| Location | London, England | Menlo Park, California |
| Companies using it | ||
| Contact info |
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