perspective VS cylon

Why do you want to render to canvas?

Perspective seems to be the most performant html table. It is more focused on extremely fast updates than styling, although it looks good.

Glide is a newcomer that also renders to canvas.

https://github.com/finos/perspective

https://github.com/glideapps/glide-data-grid

SQL workbench also uses https://perspective.finos.org/ for tables. It's a WASM table library which pairs nicely with duckdb and works well with large tables.

Yes. We are working on adding support for aggregation and pivoting using https://github.com/finos/perspective

I haven't looked extensively at react-datasheet. It looks like it is trying to build more of a full product than the other data tables.

I have used ag-grid extensively, its an impressive product. Some pieces are a little awkward to use, particularly auto-sizing. But generally ag-grid has thought of most functionality and has a solution. The creator of ag-grid had a great interview on Javascript Jabber [1].

The other serious data table component that I have seen is FinOS Perspective [2]. This is extremely high performance, also more specialized and probably harder to customize. I think Perspective renders to a canvas element from Rust/C++ compiled to WASM (not 100% sure). It is also made for streaming updates.

AG-Grid supports streaming updates... but only in the commercial version.

Eventually the data model for these types of tables becomes tricky. I will be investigating parquet-wasm for my use case. Hit me up if you want to collaborate.

[1] https://blog.ag-grid.com/javascript-jabber-podcast/

[2] https://perspective.finos.org/

Something like https://github.com/finos/perspective ? We use an OLAP(-y) WASM engine to provide query-ability to our data visualization tool, and doing the calculations in the browser is cheaper and simpler than a server-side database for datasets that fit in browser memory.

There's also https://cylondata.org/ which is more of a Pandas approach.

I'd like to introduce Cylon, a fast, scalable, distributed-memory-parallel runtime. From v0.4 release onward, Cylon introduces a "Pandas-like DataFrames for MPI environments"! It is now available Cylon v0.4.0! :-) This is, by far our most significant release.

Cudf and Cylon are two execution engines natively supporting Arrow format https://github.com/rapidsai/cudf https://github.com/cylondata/cylon