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Editor’s note: The Wherobots Spatial Data Catalog is now the Havasu Catalog.
The general availability of the Overture Maps Foundation’s Global Entity Reference System (GERS) makes it a lot easier to build intelligence about features of our physical world.
You can think of a GERS as a system for applying a unique key to physical features in the world. Overture assigns GERS IDs to millions of features in their data products, such as office buildings, highways, countries, rivers, schools, and more. Using GERS IDs, you can more easily join datasets to build a more complete view of physical-world features in space and measure relationships over time.
Key benefits of GERS IDs include:
You can read more about GERS IDs in Overture’s documentation.
At Wherobots, we’re proud to be a member of the Overture Maps Foundation, supporting the project since its formation, and as an official member since 2024. We also host and manage all of Overture’s recent datasets in the Wherobots Spatial Catalog, and they are offered at no additional cost to all customers. These datasets are production ready and at your fingertips.
Select * from wherobots_open_data.overture.buildings_building
New Wherobots customers can get started with Overture’s datasets in the free-to-use Community Edition, and graduate to the Professional edition when they want to join Overture data with their data in cloud storage.
A key design goal of GERS is to simplify how organizations can join and enrich their own datasets using canonical Overture datasets. Wherobots makes this vision real by providing built-in support for the GERS schema, enabling users to easily query, filter, and join to valuable geospatial datasets using GERS IDs, and through the use of spatial join predicates available in Apache Sedona and Wherobots. Whether data teams are working with parcel boundaries, retail site locations, road networks, or foot traffic telemetry, Wherobots makes it easy to enrich data using GERS with SQL or Python.
Overture GERS Schema Extension Paths (not exhaustive)
Stay tuned for a new tutorial from Wherobots that shows you how to use GERS IDs with Overture Places.
Wherobots was founded by the original creators of Apache Sedona, the open-source engine for distributed geospatial processing. Overture now runs many of their Apache Spark and Sedona based data pipelines on Wherobots because they run up to 20x faster, at a fraction of the cost, and the Overture team benefits from the spatial expertise we offer them as a customer. The Overture team uses Wherobots’ Apache Airflow support to trigger job runs that power production of their planetary scale datasets. This feature and Wherobots compatibility with Spark and Sedona, also made it very easy for Overture to redirect where their Airflow-orchestrated jobs ran.
“Overture produces a building dataset covering all buildings in the world, with 2.6B geometries and growing, that’s updated frequently. There’s a lot of data, and compute that goes into producing it and keeping it up to date. We accelerated the pipelines that produce the buildings dataset by up to 20x after we moved them to Wherobots, which required a simple redirection of our code. We retained compatibility with Apache Sedona, and the move put us into a development experience that’s made us more productive.” – Jennings Anderson, Geoscientist at Overture and Data Engineer at Meta.
“Overture produces a building dataset covering all buildings in the world, with 2.6B geometries and growing, that’s updated frequently. There’s a lot of data, and compute that goes into producing it and keeping it up to date. We accelerated the pipelines that produce the buildings dataset by up to 20x after we moved them to Wherobots, which required a simple redirection of our code. We retained compatibility with Apache Sedona, and the move put us into a development experience that’s made us more productive.”
– Jennings Anderson, Geoscientist at Overture and Data Engineer at Meta.
We’re committed to improving open standards in the geospatial data ecosystem. Wherobots is a leading contributor of spatial type support in Apache Iceberg and Parquet, the most popular open table and file formats for the cloud data lakehouse, to make it easier for companies to utilize geospatial data.We’ve partnered with Overture to improve the foundation for a scalable, versioned, and queryable world of features backed by GERS. By modernizing how geospatial data is accessed in the cloud via spatial data type support in Iceberg and Parquet, and improving accessibility and utility of open map data via GERS, we believe new use cases for spatial data will emerge to improve business operations, research, and our way of life.
The launch of GERS is a big step for advancing spatial intelligence, and a leap toward a more open, interoperable data ecosystem. Wherobots is proud to be part of this journey, and we’re excited to continue supporting the Overture mission through operational pipelines, open standards, and accessible tools.If you’re building with geospatial data, we invite you to explore how Wherobots can help you take full advantage of GERS by easily joining your first party data with the GERS ID system.
Next steps
Key takeaways
The Global Entity Reference System assigns persistent unique IDs to physical-world features in Overture data products. Those IDs let you join and enrich datasets that refer to the same building, road, place, or other entity over time.
Wherobots hosts and manages recent Overture datasets in the Spatial Catalog at no additional cost. New users can start on free Community Edition and move to Professional when they need to join Overture to their own cloud storage.
Yes. Jennings Anderson (Overture / Meta) says the global buildings pipeline—2.6 billion geometries, updated frequently—got up to 20x faster after jobs were redirected to Wherobots, keeping Apache Sedona compatibility and using Wherobots Airflow job runs.
Use GERS IDs and spatial join predicates in Apache Sedona/Wherobots SQL or Python against Overture tables such as wherobots_open_data.overture.buildings_building. A follow-on Places tutorial is previewed in this post (later published separately).
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