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A Hands-On Guide for Working with Large-Scale Spatial Data. Learn more.
This is the first post in a series that will introduce Wherobots Cloud and WherobotsDB, covering how to get started with cloud-native geospatial analytics at scale.
Wherobots Cloud is a fully managed cloud platform that enables developers and data scientists to efficiently manage their spatial analytics and AI pipelines in the cloud. The core of Wherobots Cloud is powered by Apache Sedona and WherobotsDB, a scalable geospatial analytics database engine. WherobotsDB is built on a distributed compute architecture which enables scalable computation of massive datasets without sacrificing speed. With an architecture that separates the compute layer from the storage layer WherobotsDB is truly cloud-native.
WherobotsDB is built upon the open-source Apache Sedona project that provides the foundation for scalable geospatial analytics. By leveraging WherobotsDB in Wherobots Cloud developers and data scientists can take advantage of optimized query processing, a data lakehouse architecture built on Havasu – an Apache Iceberg-compatible spatial table format– with a self-service fully-managed cloud environment.
You can get started with Wherobots Cloud for free – no credit card required – with a generous free tier. Sign up at cloud.wherobots.com.
Once you’ve signed in to your Wherobots Cloud account you’ll be able to view your account dashboard, notebooks, scheduled jobs, and files. Creating a notebook environment is the first step to getting started with WherobotsDB. With the Wherobots free tier you’ll have access to a default resource configuration which can be expanded by signing up for the Wherobots Professional Tier.
Once you’ve started the notebook environment click “Open” to launch JupyterLab. The Jupyter notebook environment will be your main interface for working with WherobotsDB via Python or Scala. You can create your own Jupyter notebook to begin your geospatial analysis workflow or explore the many sample notebooks via the file explorer in the left tab. Example notebooks are available to show how to work with both vector and raster data via Spatial SQL, how to access the Wherobots open data catalog, how to leverage the Havasu spatial table format, and much more.
You can also upload notebooks shared by others via platforms like GitHub, for example this repository includes a few notebooks from some of my recent projects.
In addition to the Wherobots open data catalog, WherobotsDB is able to import data from virtually any spatial data format including flat files, Shapefiles, GeoJSON, GeoParquet, and PostGIS databases. Included with your Wherobots Cloud account is free private file hosting via AWS S3. You can upload and manage files via the “Files” tab in Wherobots Cloud. Once uploaded you’ll be able to access files via a private S3 URL making the files available to only accounts in your Wherobots Cloud organization.
The Wherobots Online Community is the place to ask questions, learn what others in the community are building with Wherobots and Apache Sedona, and share your spatial expertise with the community. Please join the community and connect with others interested in the exciting world of spatial data analysis.
You can find documentation for all things WherobotsDB and Wherobots cloud at docs.wherobots.com. The documentation includes information and examples covering how to further configure and manage your Wherobots Cloud account as well as how to leverage WherobotsDB’s rich Spatial SQL and Python APIs for working with geospatial data in the cloud.
Another helpful resource is the Wherobots YouTube channel for technical videos and hands-on livestreams showing what’s possible with Apache Sedona & Wherobots Cloud
Key takeaways
A fully managed cloud for spatial analytics and AI. WherobotsDB, built on Apache Sedona, is the scalable geospatial database engine, with compute separated from storage and a Havasu (Iceberg-compatible) lakehouse format.
Yes. Sign up at cloud.wherobots.com with no credit card. The free tier includes a default notebook resource configuration and private S3 file hosting; Professional Tier expands resources.
Start a notebook environment from the dashboard, open JupyterLab, and use Python or Scala against WherobotsDB. You can create a blank notebook or use the sample notebooks in the file explorer.
The post lists flat files, Shapefiles, GeoJSON, GeoParquet, and PostGIS databases, plus the Wherobots open data catalog and files you upload to the private S3 bucket.
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