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SERIES4 OF 4 PUBLISHED

Geospatial in Cloud

Four dated technical notes on Databricks, AWS, GCP, and Snowflake for geospatial workloads. Retained illustrations are labelled. Current claims require a target run record, current vendor sources, and human review.

4 parts
59 min total
PLATFORMS:
Databricks
AWS
GCP
Snowflake
1
AVAILABLE15 min

Geospatial in Cloud: Databricks

A dated technical note on Databricks spatial workflows, lakehouse boundaries, and checks for a target runtime.

  • -Mosaic and spatial SQL boundaries
  • -H3 indexing patterns
  • -When to test another runtime
2
AVAILABLE15 min

Geospatial in Cloud: AWS

A dated technical note on AWS building blocks, COG access, spatial SQL, orchestration, and workflow-specific validation.

  • -Glue and Step Functions boundaries
  • -Lambda, S3, and COG pattern
  • -Athena spatial SQL checks
3
AVAILABLE15 min

Geospatial in Cloud: GCP

A dated technical note on BigQuery geography, Earth Engine, Dataproc, Cloud Run, and target-workflow checks.

  • -Dataproc processing boundary
  • -BigQuery geography functions
  • -Earth Engine integration checks
4
AVAILABLE14 min

Geospatial in Cloud: Snowflake

A dated technical note on Snowflake spatial types, H3 functions, SQL workflows, limits, and validation boundaries.

  • -H3 indexing patterns
  • -Warehouse and account boundaries
  • -When to test another runtime
BEGIN THE SERIES

Start with Part 1:
Databricks for Geospatial

Start with the retained Databricks note, then compare the platform boundaries and validation questions across AWS, GCP, and Snowflake.

Read Part 1: DatabricksDiscuss a workflow
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