Struggling to choose between Google Maps Engine and QGIS? Both products offer unique advantages, making it a tough decision.
Google Maps Engine is a Travel & Location solution with tags like maps, location, geographic-data, visualization.
It boasts features such as Upload and store geospatial data, Visualize data on interactive maps, Perform analysis and make measurements, Share maps and collaborate, Develop custom web and mobile map applications and pros including Powerful and intuitive mapping capabilities, Integration with other Google services, Scalable cloud infrastructure, Collaborative features, Free tier available.
On the other hand, QGIS is a Office & Productivity product tagged with gis, mapping, geospatial-data, data-visualization.
Its standout features include Desktop GIS application, View, edit, analyze geospatial data, Create maps with many layers, Plugin architecture for extensibility, Supports many vector and raster formats, Powerful styling and labeling capabilities, Geoprocessing tools, Print layouts for map production, Python console for automation and customization, and it shines with pros like Free and open source, Cross-platform (Windows, Mac, Linux), Active development community, User friendly graphical interface, Support for GRASS, SAGA, GDAL libraries, Can handle large datasets, Many plugins available, Integrates with PostgreSQL/PostGIS databases.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
Google Maps Engine is a cloud-based mapping platform that allows users to store, visualize and share geographic data. It provides tools to create custom maps by uploading data or connecting to external sources.
QGIS is a free and open-source geographic information system software. It allows viewing, editing, and analyzing geospatial data. QGIS offers features for mapping, data management, and data visualization.