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Top 4 Rust Data processing Projects
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rust-ndarray
ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
I would love some examples of how to do non-trivial data interop between Rust and Python. My experience is that PyO3/Maturin is excellent when converting between simple datatypes but conversions get difficult when there are non-standard types, e.g. Python Numpy arrays or Rust ndarrays or whatever other custom thing.
Polars seems to have a good model where it uses the Arrow in memory format, which has implementations in Python and Rust, and makes a lot of the ndarray stuff easier. However, if the Rust libraries are not written with Arrow first, they become quite hard to work with. For example, there are many libraries written with https://github.com/rust-ndarray/ndarray, which is challenging to interop with Numpy.
(I am not an expert at all, please correct me if my characterizations are wrong!)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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ux-dataflow
UX-Dataflow is a streaming capable data multiplexer that allows you to aggregate data and then process it using a Chain of Responsibility design pattern.
Rust Data processing related posts
- Some Reasons to Avoid Cython
- Stream processing framework for a new project in Python
- Helper crate for working with image data of varying type?
- A Python package for streaming synthetic data
- What is the most efficient way to study Rust for scientific computing applications?
- Snowflake - what are the streaming capabilities it provides?
- faer 0.8.0 release
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Index
What are some of the best open-source Data processing projects in Rust? This list will help you:
Project | Stars | |
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1 | rust-ndarray | 3,235 |
2 | mech | 198 |
3 | utah | 141 |
4 | ux-dataflow | 8 |