Awesome
ninjabook
A lightweight and high-performance order-book implemented in Rust, designed to process level 2 and trades data.
Available in Python and Rust!
Getting started
Find Python and Rust hello_world programs in the examples directory.
Performance
Ran a couple of benchmarks showcasing real case scenarios against a naive Vec implementation and an orderbook with a fixed size of 500 levels.
The benchmarks are run with 300,000 events of level 2 orderbook data . This data is split in 2 chunks:
- First 200,000 events are used to warm up and verify all orderbook versions publish the same BBO and top5 levels.
- Last 100,000 for the actual benchmark.
The scenarios tested are:
- Process events and stream best bid and ask
- Process events and stream top5 bids and asks
Here are the results:
| bench | iterations | time | ns/iter |
|---|---|---|---|
| ninjabook_bbo | 100,000 | 5.0108 ms | 50.108 ns |
| fixed_500_bbo | 100,000 | 49.018 ms | 490.18 ns |
| naive_bbo | 100,000 | 90.552 ms | 905.52 ns |
| ninjabook_top5 | 100,000 | 11.797 ms | 117.97 ns |
| fixed_500_top5 | 100,000 | 54.693 ms | 546.93 ns |
| naive_top5 | 100,000 | 95.644 ms | 956.44 ns |
Contributing
To add a better version, create a new file, implementing the same methods as orderbook.rs (including tests) and add the improved orderbook to the bench optimal_vs_naive.rs. Only order books with a better performance than orderbook.rs will be considered. Lastly, add performance logs to the Pull Request, can just copy paste what cargo bench outputs.
Any issues, refactoring, docs and tests are also welcomed. Feel free to reach out here if you have any questions.
Caveats
Just some cosmetic improvements need to be done. Refactor Orderbook core functions into a Trait, add docs and potentially more tests/bench/examples.