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.
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/