Spatial SQL
Course Index
37 Lessons · 3 Levels
Complete Spatial SQL roadmap — BigQuery, Snowflake, SQL Server, DuckDB, Redshift, Apache Sedona, H3/S2 grids, BI dashboards, and real cross-platform spatial analysis builds.
37Lessons
3Levels
4Projects
FreeAccess
Level IFoundations & ConceptsLessons 1–11
Lesson 01
What is Spatial SQL?
Lesson 02
Spatial SQL vs PostGIS
Lesson 03
The 2026 Spatial Database Landscape
Lesson 04
Geometry vs Geography Data Types
Lesson 05
WKT, WKB & GeoJSON Formats
Lesson 06
Core Spatial Functions Overview
Lesson 07
Spatial Relationships & Predicates
Lesson 08
Measurements: Distance, Area & Length
Lesson 09
Coordinate Systems & SRID Handling
Lesson 10
Spatial Indexing Concepts
Lesson 11
Choosing the Right Spatial Database
Level IICross-Platform Spatial SQLLessons 12–26
Lesson 12
BigQuery GIS: Getting Started
Lesson 13
BigQuery: Point-in-Polygon Queries
Lesson 14
BigQuery: Spatial Joins at Scale
Lesson 15
BigQuery Public Datasets for GIS
Lesson 16
Snowflake Spatial & H3 Indexing
Lesson 17
SQL Server Spatial Data Types
Lesson 18
SQL Server: Spatial Indexes & Queries
Lesson 19
DuckDB Spatial Extension
Lesson 20
DuckDB: Local Analysis with GeoParquet
Lesson 21
AWS Redshift Spatial Functions
Lesson 22
Apache Sedona for Big Spatial Data
Lesson 23
Cross-Database Query Patterns
Lesson 24
Aggregations & Spatial Clustering in SQL
Lesson 25
Working with Census & Demographic Data
Lesson 26
Query Performance & Cost Optimization
Level IIIAdvanced & ProjectsLessons 27–37
Lesson 27
Connecting Spatial SQL to QGIS
Lesson 28
Connecting Spatial SQL to Python
Lesson 29
Visualizing Spatial SQL Results
Lesson 30
Spatial SQL for Dashboards & BI Tools
Lesson 31
Hexagonal Grids: H3 vs S2
Lesson 32
Machine Learning with Spatial SQL
Lesson 33
Spatial SQL Best Practices & Anti-Patterns
Lesson 34
Build a Census Demographics Analysis
Lesson 35
Build a Multi-City Retail Site Analysis
Lesson 36
Build a Logistics Route Optimization Query
Lesson 37
Build a Real Estate Market Analysis