Hi @AyanPalit,
Thanks for your response.
I’ve been reviewing Wherobots, which is built on top of Apache Sedona to enable big data processing for GIS datasets using Spark. Its capabilities around Spatial ETL, Analytics, and GeoAI look promising, particularly in the context of handling large-scale geospatial workloads.
My main interest is in exploring how we can delegate heavy GIS workloads to Spark-style clusters for faster processing.
I’m already familiar with ArcGIS Notebooks, and while they allow Data Scientists to work with ArcGIS data, I ran into limitations when trying to access and process very large volumes of data directly.
What I’d like to understand better is:
How can these developments (e.g., Sedona/Wherobots) be integrated into the ArcGIS ecosystem?
Is there a way to make them work side by side without having to constantly move large datasets between systems?
Since data sizes are massive, minimizing duplication and movement is key.
I’d love to hear from other community members: Have you tried similar approaches? What are your use cases, challenges, or integration patterns between Spark-based geospatial frameworks and ArcGIS?
Regards,
Venkat
