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@ -17,5 +17,15 @@ But that constant factor on top of your fast key/value database is a low price t
See https://sequentialread.com/building-a-spatial-index-supporting-range-query-using-space-filling-hilbert-curve
for more information.
## Benchmarks
The benchmarks are [part of this repository](https://git.sequentialread.com/forest/modular-spatial-index-demo-opengl/src/branch/master/benchmark).
I benchmarked the spatial index against a tuned version of the "One range query for every row in the rectangle" approach I talk about in my blog post linked above, which I am calling the `Sliced` index, with various slice sizes.
For a test dataset, I used [goleveldb](https://github.com/syndtr/goleveldb) to store approximately 1 million keys, each with a 4-kilobyte random value. During the benchmarks, each database index was approximately 3.5GB in size, and the test application was consuming about 30MB of memory.
![](benchmarks.jpg)
MIT license

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