What are the analogues of hadoop for small amounts of data?

Question

open source

Now I am thinking over the software architecture where it will be necessary to receive data and store it after processing it.
There will be a maximum of 2-3 TVs of data and they will come in small portions within 3-5 years.
There will be only one server, so doubts have leaked out whether it would be appropriate to use hadoop, while it looks like running a Boeing for pizza delivery.
That's why I became interested in the question of which can be analogues?
What are the appropriate options for this amount of data?
And if it is worth taking hadoop, then what configurations will be suitable?

Answer 1

Apache Spark is essentially an analogue (the same Map Reduce).
Well, for processing and storage: NumPy and Pandas.
Visualization: Mathplotlib, seaborn.
PS This is all the Python stack.