datafuse VS arrow2

v0.4.102-nightly

Datafuse is currently in Alpha and is not ready to be used in production, Roadmap 2021

v0.4.95-nightly

1. With the improvement of the rust ecosystem, using rust has made database development faster and easy, for example datafuse use the tokio to implement the pipeline https://github.com/datafuselabs/datafuse/tree/master/fuseque....

2. Couldn't agree with you more with easier-to-manage as a first-class feature, but some times easier-to-manage is built on stability, that's what datafuse is trying to do.

Datafuse – Modern Real-Time Data Processing in Rust\ (8 comments)

Datafuse even borrows code from datafusion, which makes the name choice seem intentionally confusing. https://github.com/datafuselabs/datafuse/issues/654

Datafuse - A Modern Real-Time Data Processing & Analytics DBMS with Cloud-Native Architecture, built to make the Data Cloud easy. Written in Rust.

One of the interesting components of Polars that I've been watching is the use of the Apache Arrow memory format, which is a standard layout for data in memory that enables processing (querying, iterating, calculating, etc) in a language agnostic way, in particular without having to copy/convert it into the local object format first. This enables cross-language data access by mmaping or transferring a single buffer, with zero [de]serialization overhead.

For some history, there's has been a bit of contention between the official arrow-rs implementation and the arrow2 implementation created by the polars team which includes some extra features that they find important. I think the current status is that everyone agrees that having two crates that implement the same standard is not ideal, and they are working to port any necessary features to the arrow-rs crate and plan on eventually switching to it and deprecating arrow2. But that's not easy.

https://github.com/apache/arrow-rs/issues/1176

https://github.com/jorgecarleitao/arrow2/pull/1476

https://github.com/jorgecarleitao/arrow2 https://github.com/apache/arrow-datafusion https://github.com/apache/arrow-ballista https://github.com/pola-rs/polars https://github.com/duckdb/duckdb

Currently datafusion and polars aren't directly operable iirc because they use different underlying arrows implementations, but there seems to be work being done on that here https://github.com/jorgecarleitao/arrow2/issues/1429

[arrow2](https://github.com/jorgecarleitao/arrow2) and [parquet2](https://github.com/jorgecarleitao/parquet2) are great foundational libraries for and DataFrame libs in Rust.

[1] https://github.com/jorgecarleitao/arrow2

In lockstep with arrow2's 0.13 release, we have published polars 0.23.0.

This is so freaking life-saving! - we have been using StreamingIterator and FallibleStreamingIterator in libraries (arrow2 and parquet2) and the existing landscape is quite confusing for new users!

arrow2 has support for mssql via ODBC (which microsoft has first class support to). Here are the integration tests we have (both read and write) against mssql specifically.