An Inside Look at Cloud-Native Geospatial Formats

The geospatial industry is currently undergoing a wave of rapid innovations based on a number of new geospatial data formats that have been designed from the ground up to leverage the capabilities of the cloud.

We expect these cloud-based innovative advancements to benefit a wide range of geospatial users. And to provide a world-class, premier location intelligence platform, Foursquare actively participates in the ongoing innovation.?

This post gives you a peek at our notes, sharing our thoughts on how the geospatial community can utilize new technologies and how products like Foursquare’s can help users adopt the tools and workflows of this new ecosystem.

Cloud-Native Geospatial Formats

Or… what would the geospatial world look like if we built everything from the ground up on the cloud?

The geospatial industry has always been characterized by the massive size of geospatial datasets.?

Let’s go way back to 1972, when NASA’s first Landsat satellite flew with a set of 76-pound cameras with 1km of film… roughly amounting to 3.75 gigs of storage. Unfortunately, two-thirds of the data collected between 1972-1999 was rendered inaccessible due to the film format, downlinking to ground stations, and other hardware issues.

We have come a long, long way. Modern data storage, the internet, the proliferation of open source tooling, and the development of spatial databases allow us to study millions of layers that make up our planet.

Back to 2024… Why do we need new geo formats? What trends are we seeing in the last five years that we didn’t see 10 years ago?

Short answer:?The availability of cheap, reliable, and scalable cloud storage is enabling new, more efficient and flexible ways of working with geospatial data.?

Traditional databases and service providers are on the verge of becoming unnecessary overhead for accessing massive geospatial datasets. New cloud-native data formats have emerged that let us efficiently access data from cloud storage.

Below is a selection of cloud-native geospatial formats we believe are becoming cornerstones of the industry.?

A common theme in the above formats is that they are designed to store data in single, very large (“larger than memory”) files that offer some form of internal structure (whether row groups, row ranges, internal tiles, etc.) that allows clients to load only the “chunks” of the file containing the data they need.

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