When to use distributed and when to use one server

There is a complexity cost to distributed computing though. It is not as simple as single server analytics. Even though the frameworks handle a lot of the complexity for you, you still have to think and design your analytics to work across multiple nodes.

Here are some guidelines on when to keep it simple and on one server:

• There is not much need for scale: Your analytics process needs little change even if the number of IoT devices and data explodes. For example, the analytics process runs a forecast on data already summarized by month. The volume of devices makes little difference in that case.
• Small data instead of big data: The analytics run on a small subset of data without much impact from data size. Analytics on random samples is an example.
• Resource needs are minimal: Even at orders of magnitude more data, you are unlikely to need more than what is available with a standard server. In this case, keep it simple.