One use case could be a data visualization similar to what I built in [1] To build the visualization in [1], I used 3 datasets in csv format from a kaggle comp

One use case could be a data visualization similar to what I built in [1] To build the visualization in [1], I used 3 datasets in csv format from a kaggle competition [2], and I implemented the charts using dc.js and Leaflet.js. The charts were interactive and I could managed to filter the data even in the map. The largest dataset was 284 MB, which was still ok and didn't crash my browser. There were 2 drawbacks to my approach: 1- All the data was in the browser. If my data was bigger (~1GB), then it would crash my browser. 2- If I deploy the visualization to a server (for example AWS), then it would make the rendering extremely slowly as it has to download all the data to the browser... [1] http://adilmoujahid.com/posts/2016/08/interactive-data-visualization-geospatial-d3-dc-leaflet-python/ http://adilmoujahid.com/posts/2016/08/interactive-data-visua... [2] https://www.kaggle.com/c/talkingdata-mobile-user-demographics/data https://www.kaggle.com/c/talkingdata-mobile-user-demographic...