I have not seen a better mapping tool than CartoDB. You get the familiarity of Google Maps with arbitrarily complex geographic data visualization on top. CartoDB excels at large data sets where Google Maps API completely chokes when attempting to handle more than ~1000 data points. I was able to plot 500,000 points on a map with reasonable speed and able to perform complex aggregations to display boundaries of areas containing certain types of data, intersections of those sections, and more.
QGIS is free and very easy to install, and no license is required. Not having to deal with licensing issues has saved me considerable time and frustration.
The QGIS help community is very active, and it is easy to find answers. Although QGIS does not offer support in the way that ArcMap does, I was always able to google my question and find either a tutorial or website that solved my problem.
QGIS seems to crash less often than ArcMap. It is super annoying to have a program crash when you are in the middle of a project, but I have not had any issues with QGIS. Also, QGIS is updated frequently.
Learning curve - CartoDB might be difficult to use if you don't have a bit of SQL or data structures background. If you're not familiar with floats, strings, etc., you might upload an Excel file and be confused about how to manipulate it to get the software to create the maps that you want.
Performance - When I used it, there were some occasional issues with loading and parsing large data files.
QGIS is hard to use for beginners. A better tutorial and clearer online tutorials could improve this.
Labeling interface is overly complicated. Allowing users to manually add labels to relevant items could be helpful.
QGIS should have more "wizards" that can easily import common data points (median income, population density, etc) and cross tabulate that with other categories easily from uploaded data.
I wasn't a GIS user at all when I started using QGIS, nor did I have any background working with data in anything other than Excel, and as a result, I struggled quite a lot in the beginning (it's not quite Google Maps). But having said that, I haven't come across anything that I couldn't do with a little help from the online community. I've done complex spatial analyses on large datasets of metropolitan cities, designed custom multi-page pdf reports that automatically cycle through different areas of an area, etc.
And the GIS staff that I've appointed, after their initial resistance, took to the tool like a fish to water, and I haven't heard them complain after starting to use the tool for a week or two.
But if you're new to GIS, be patient and invest some time to learn how to use the tool. It is absolutely worth it.
Even though there is a no dedicated support team for QGIS (or at least we are not aware of it), there is a huge online community and a large number of forums catering to every question you may have regarding any particular functionality of QGIS. So, you have a lot of help available but you will have to sift through it on the web.
Python is definitely a more powerful tool for data munging and analysis, but the python packages for geo-related data viz (bokeh, matplotlib, seaborn) are cumbersome to use. I would recommend doing your data analysis in Python and then exporting the final data to CartoDB for visualization. One benefit of doing this is that CartoDB can automatically publish your viz to a link or object, so you don't have to export it and host it yourself. Another benefit is that CartoDB automatically updates the viz once you change the data, eliminating the need to continuously regenerate image files. I haven't used Tableau too extensively, but from the experience I've had with it -- Tableau is better suited for traditional analytical visualization (charts, graphs, etc.) than for geospatial mapping and visualization.
QGIS is open source and freely available for Windows and Mac iOS Geographic Information System Software. QGIS is highly customizable as per project requirements and different application usage. QGIS has ample tools and plugins that are useful for the analysis of raster and vector data. It also supports GRASS, GDAL, and SAGA tools.
We can ingest data in any format, and convert it to industry-standard spatial files for hosting on our online GIS platform.
Many client projects require us to analyze and understand data before we can report on it.
Because QGIS is free, and the learning curve is negligible for bright GIS technicians, the ROI is practically infinite because the investment is basically zero.
