Here’s the difference between Apache Spark and Count. The comparison is based on pricing, deployment, business model, and other important factors.
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
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 | ||
---|---|---|
Categories | Data Modelling and Transformation | Data Workspace/ Collaboration |
Stage | Late Stage | Mid Stage |
Target Segment | Mid Size, Enterprise | Mid Size, Enterprise |
Deployment | On Prem | SaaS |
Business Model | Open Source | Commercial |
Pricing | Freemium | Freemium, Contact Sales |
Location | US | London, England |
Companies using it | ||
Contact info |