arquero

You can get a long way nowadays with Arquero[0] and Observable[1]. Arquero allows columnar based data storage and processing, with a grammar of data processing verbs similar to e.g. dplyr. Not as fast as vectorized computations in e.g. Python or R, but faster than has previously been possible. I'm not suggesting these are the first tools you'd reach for for data science in production, but I've found them extremely useful for prototyping, experimenting with algorithms, and visualization. I think it's got to the stage they should be seriously considered for some types of relatively simple data processing work due to their ease of deployment. [0]https://github.com/uwdata/arquero [1]https://observablehq.com/

There is a Typescript arrow library that can operate off the IPC format. As an example use case, take a look at the arquero data processing library from the University of Washington (from the same group that created D3). https://github.com/uwdata/arquero

Arrow is definitely one of the top 10 new things I'm most excited about in the data science space, but not sure I'd call it the most important thing. ;) It is pretty awesome, however, particularly for folks like me that are often hopping between Python/R/Javascript. I've definitely got in on the roadmap for all my data science libraries. Btw, Arquero from that UW lab looks really neat as well, and is supporting Arrow out of the gate (https://github.com/uwdata/arquero).