Here’s the difference between Google BigQuery and Count. The comparison is based on pricing, deployment, business model, and other important factors.
BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011.
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.
Overview | ||
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Categories | Data Warehouses | Data Workspace/ Collaboration |
Stage | Late Stage | Mid Stage |
Target Segment | Enterprise, Mid size | Mid Size, Enterprise |
Deployment | SaaS | SaaS |
Business Model | Commercial | Commercial |
Pricing | Contact Sales | Freemium, Contact Sales |
Location | US | London, England |
Companies using it | ||
Contact info |