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[ep 12] Spatial Data Application | Demo | The Cockroach Hour

Spatial data powers some of the world’s most innovative apps and services, letting you answer questions like, “Where’s the nearest gas station?” and “How long will it take for my ride-sharing vehicle to arrive?” and even, “Where can I catch a Pokémon?”

And in this video we'll show you how to build a spatial data application. CockroachDB is the first SQL database to build spatial data functionality from the ground up for a distributed environment. This means you can now effortlessly scale your spatial data and have the confidence it will survive outages.

In this episode of the Cockroach hour, we will cover:

  • Geometry and Geography types
  • Spatial Indexing • PostGIS-compatible built-ins and functions
  • Complete tech stack for building a spatial data application
  • Live demo of a rolling upgrade with no downtime


00:00 CockroachDB's decision to build support for Spatial Data

00:36 What is Spatial Data?

1:55 How CockroachDB built support for spatial data

5:50 How to build a spatial data application: Spatial Data Demo of a spatial data app built with Python Flask and CockroachDB

15:00 What data is used to build a spatial application?

15:50 Github repository for all the code used in the spatial data application

16:45 the CockroachDB consul

17:35 Live demo of a rolling upgrade

23:30 Building spatial data support in Go

25:05 How close is the PostGIS library to the CockroachDB spatial data library?

27:12 Is there a benchmark that compares Postgres to CockroachDB?

28:58 The great thing about Spatial Data and Kubernetes - How to scale a spatial data application in CockroachDB

30:28 What is the benefit of running a spatial database on Kubernetes?

33:29 Can a spatial data application on CockroachDB survive region failures?

34:50 Pinning data to a location for low latency

35:55 How do geospatial indexes work?

37:20 Spatial Data is open source

39:15 What applications do people use spatial data for?

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