Benchmark geospatial query performance on NoSQL(-like) databases

The full paper can be found in Releases. Source paper can be found at report.typ. You may want to compile it with typst.

Test Environment

• Databases
  • MongoDB Enterprise Server@latest
  • Redis (Stack)@latest
• Programming Language and lib
  • TypeScript
    • Mongoose
    • node-redis
    • Redis OM
• Host
  • GitHub Codespaces
  • GitHub Actions

Run Benchmarks

npm run start [-- [options]]

  -t, --type <type>     type of dataset ["inat2017", "random", "grid", "cluster"] (default: "inat2017")
  -c, --count <count>   number of data points (default: "100000")
  -r, --repeat <count>  number of repeat (default: "1")

Test dataset

By default, this benchmark uses iNaturalist 2017's Fine Grained Geolocation Datasets (visipedia/fg_geo). Which contains 654,818 records of geolocation point.

File was placed at datasets/inat2017/inat2017_file_name_to_geo.csv with header.

Format:

filename,latitude,longitude

We also provide 3 other runtime generated datasets:

• Random
  • Points are totally placed by RNG.
• Grid
  • Points separated evenly around the earth.
  • Using Fibonacci sphere algorithm.
• Cluster
  • Every 50 points will be placed together with a bit offset as a cluster, and all clusters will be distributed randomly.

Test queries

• Data should be loaded into the database before running the queries.
  • Warm up index is allowed.
  • Warm up query is not allowed.
• Storage cost will be calculated.
  • For memory-storage databases, both memory and persist storage cost will be calculated.
• In theory, all databases should return the same result.

Basic test requires all queries runs one by one in a single process/thread.
Advanced test allows queries to run in parallel, and allows to optimized for test host.

Query A: Find nearest location

Pick a random location, find the closest location in the dataset.

Query B: Find locations within a radius

Pick a random location from the dataset, find all locations within certain distance.

Query C: Find locations within a radius and order them.

Pick a random location from the dataset, find all locations within certain distance, order by distance.

License and Citation

This project is licensed under the terms of the CC BY-SA 4.0 license.

To cite this report, check CITATION.cff.