SQL Geometry type and Geography type conversions/projections

SQL Geometry and Geography Types: Making Sense of Maps in Your Database

Spatial data is no longer some futuristic concept; it’s a here-and-now necessity for databases dealing with anything from delivery routes to demographic analysis. SQL Server, along with other database powerhouses like PostGIS and Snowflake, arms you with two key spatial data types: Geometry and Geography. But what’s the real difference, and how do you wrangle them to play nice together? Let’s dive in.

Geometry vs. Geography: Flat Earth or Round Earth?

Think of it this way: Geometry is like drawing shapes on a flat piece of paper. It assumes a Euclidean, or flat, coordinate system. Perfect for local maps or building plans where you don’t need to worry about the Earth’s curve. It’s also generally faster to work with, which is a definite plus.

Geography, on the other hand, knows the Earth is round. It uses a round-earth coordinate system, taking that pesky curvature into account. This is the choice for anything spanning significant distances, like calculating flight paths or analyzing global weather patterns. Trying to use Geometry for that? You’re going to have a bad time.

Choosing the right type is all about context. Need to find the closest coffee shop in your neighborhood? Geometry’s your friend. Planning a cross-country road trip? Geography all the way.

Converting Between Geometry and Geography: Bridging the Gap

So, what happens when your data lives in both worlds? Maybe you’re merging datasets or your project’s needs evolve. That’s where conversion functions come in handy. SQL provides tools to translate between Geometry and Geography types, though it’s not always a straight shot.

• ST_AsText() and ST_GeomFromText() / ST_GeographyFromText(): These are your go-to functions for converting to and from Well-Known Text (WKT), a human-readable format for spatial data. Think of it as the “plain English” of spatial coordinates.

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