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Microsoft’s Planetary Computer vs. Google Earth Engine: A Compare and Contrast

Microsoft’s Planetary Computer vs. Google Earth Engine: A Compare and Contrast

Traditional geospatial analysis involves working with locally hosted raster and vector data that has been downloaded from a source, and stored on the hard drive of the processing machine. As the needs and capabilities of technology expand, it has become necessary to outsource both data storage, and computation to the cloud, allowing users to work with larger datasets, and save on time and processing power. Multiple advanced platforms are emerging to meet this need. 

Google Earth Engine (GEE) was launched in 2010, making it the first online data repository of its kind. Not only did it host massive amounts of satellite imagery, but it also enabled users to leverage the Google cloud to conduct processing and analysis on that data. This eliminates the need for local computing power, or specific software on the part of the user.

More Information about Google Earth Engine Here

In May of 2022, Microsoft released it’s Planetary Computer (PC) to the public, citing sustainability and climate change research as its motivation for making petabytes of earth observation data available online. Like Google Earth, Microsoft’s Planetary Computer isn’t just a storage mechanism; equipped with its own API and development environment, PC is a powerful tool for computation and geospatial analytics.

More Information about Microsoft’s Planetary Computer Here

Access to both Google Earth Engine and Microsoft Planetary Computer is free; users request an account using their email address. Google Earth Engine does favor academic use (registration with a “.edu” email tends to be approved immediately, whereas other users may take a few days to be approved), which means students will likely be entering the workforce with GEE experience baked into their education; coupled with its ten-year head start in the market, this appears to give GEE a distinct advantage.  On the other hand, the Microsoft suite is considerably intrenched in the corporate space, and PC will integrate seamlessly into the workflows of users of its existing cloud computing service, Azure. 

Planetary Computer is actively integrating open-source technology, which gives this service interoperability with many other tools that your organization may already be using. Microsoft wants to enable users to access the best-in-class open-source tools, as well as develop new additions.

“I believe [the geospatial open-source ecosystem] is such a valuable asset, not just in the fight for climate change, but in general,” says Rob Emanuele, a geospatial architect at Microsoft. “Anything that we’re building should try to take advantage of that as much as possible and contribute back to that as much as possible.”

The data available on these platforms is cloud-optimized and streamable. Essentially, at any given time, the service is only reading the packet of data that the user needs in that moment, which saves on computing power. The raster data available on both platforms includes everything from climate and weather data, to terrain and elevation layers, biodiversity and biomass models, and of course, satellite imagery. 

In fact, in addition to providing the raw Sentinel and Landsat imagery, Google Earth Engine provides auto-corrected and cloud-removed versions of the data as well. Google also recently released a 10m near-real-time (NRT) Land Use/Land Cover (LULC) dataset called Dynamic World as a component of GEE. 

Microsoft PC relies on the STAC (Spatiotemporal Asset Catalog) ecosystem for spatiotemporal searchability, which includes encoding metadata with a common JSON schema to specify what the data contains. This indexing mechanism helps users find exactly what data they need for analysis. You can think of it as a massive normalized database. Meanwhile, Google has a unique hierarchical nomenclature system, which makes finding specific datasets easy. 

In terms of data processing and analysis, both services have a bit of a learning curve. In Google Earth Engine, the user manipulates data using the JavaScript, Python, or REST APIs, and in the Planetary Computer, it’s done in a JupyterHub deployment, which, according to the PC documentation, “includes a set of commonly used packages for geospatial and sustainability data analysis.” The user can specify their development environment to include different configurations of CPU cores, memory, GPUs, and software. 

Keep in mind that the Planetary Computer is still in preview mode. Google Earth Engine boasts nearly instantaneous results to queries and processing tasks, whereas not enough testing has been done to get comparable claims from Microsoft. The Planetary Computer also appears to have less data in its catalog, but it is consistently growing, and its reliance on open source provides a unique service that could put it on the cutting edge of geospatial research and development. One of GEE’s shortcomings is that it is best for pixel-based analysis, so perhaps the PC will provide an opportunity for parallel processing or vector analysis; we’ll have to wait and see what it’s capable of. 

Explore some of the other similarities and differences between Google Earth Engine and Microsoft Planetary Computer in this summary table.

FeatureGoogle Earth EngineMicrosoft Planetary Computer
AccountRegister with Gmail accountRequest access via email
Data35 petabytes of satellite imagery, LULC, weather, and climate data24 petabytes of earth observation and environmental data
SearchabilityHierarchical naming structure and filtering systemRelies on STAC ecosystem
ProcessingJavaScript, Python, REST APIsJupyterHub deployment
ShareabilityShare via the cloud or export data to Google DriveCloud sharing
InteroperabilityGoogle integration & familiar UIOpen-source tools + integration with Microsoft products
PriceFree for academic and personal useFree for academic and personal use

Ultimately, choosing between the two will come down to preference, and need. For now, GEE is a more established service, optimized for academic and personal use, whereas Microsoft’s new PC is fresh on the market and may appeal to existing commercial Microsoft users. Both platforms have robust data catalogs, ample cloud storage, and significant processing power.

If you are looking for more information on Google Earth Engine, listen to our podcast episode here with Qiusheng Wu.

To learn more about the Planetary Computer, try this podcast discussion with Rob Emanuele from Microsoft.

Have a listen, and decide for yourself which is better!

Recommended Podcast Episodes

Sentinel Hub is somewhere between The Planetary Computer and Google’s Earth Engine
About the Author
I'm Daniel O'Donohue, the voice and creator behind The MapScaping Podcast ( A podcast for the geospatial community ). With a professional background as a geospatial specialist, I've spent years harnessing the power of spatial to unravel the complexities of our world, one layer at a time.