KX: Fast, Performant.
What do you like best about the product?
The fastest time-series database, we have used. The different types of join are very useful, once you learn ALL of them and their nuances. Using PyKX in the jupyter notebook, we have access to the console in a cell. This is very nice freature when debugging and proto-typing.
What do you dislike about the product?
The licensing and setup can be very difficult to manage and and maintain. Setting up PyKX, with the dual licenses available -- being open yet closed -- is confusing.
Debugging KDB+ and PyKX can be frustrating.
Debugging KDB+ and PyKX can be frustrating.
What problems is the product solving and how is that benefiting you?
The most used and very powerful freature is the window and asof joins.
We are always impressed with the speed of the results and easy of exporting to
csv's and pushing the data to other parts of the data stack.
The other important freature is the continued intergration with python .
We are always impressed with the speed of the results and easy of exporting to
csv's and pushing the data to other parts of the data stack.
The other important freature is the continued intergration with python .
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