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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

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
  • 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.