Hello,
I'm looking to implement TabPy on one of our servers. We're dealing large sets of data so optimization is important. Though the calculations and analysis can be done in SQL server through a live query, I'm looking at the TabPy alternative.
From your experience, is there an advantage in terms of performance and computing resources of using TabPy? Keep in mind, the data on the dashboard is a daily extract and TabPy calculations would be done on that extract versus joining operations on SQL server through a live query to get the same results.
Side question, specific to computing resources, is there a difference in using Tableau native calculated field versus a tabpy calculation?
Thank you.
Hi Ryder, I would say it depends on what your queries are doing. Are these queries doing calculations that can be saved once per day or do they need to be live as folks interact with your dashboards? In my experience, TabPy is on the slower side and I haven't heard much about it being used as a way to boost performance, but again it would depend on what you are using it for. When using TabPy in your calculations, or any similar external service, you are creating a table calculation that is computed after the regular aggregations are computed. This can add additional wait time on top of the time for the TabPy calculations. Can you share more about what you are thinking of using TabPy for and the type of calculations you are doing?
-Keshia
