Why streaming data matters more than it looks

This is cheap to get right at the start and expensive to retrofit. Streaming data is easy to treat as a detail, and that is exactly why it is worth a few minutes of attention.

Data outlives the applications built on top of it, which is why the model deserves more thought than the screens. Assume whoever inherits this will have half your context and none of your patience.

What it costs to ignore

Streaming is worth it when the delay costs money. Getting it slightly wrong is survivable. Ignoring it entirely is not. It is worth deciding this deliberately rather than inheriting whatever the last person set up.

Ordering and replay are the hard parts. This is the sort of thing that compounds, quietly, in both directions. Assume whoever inherits this will have half your context and none of your patience.

Common failure modes

Batch is simpler and usually enough. This is the sort of thing that compounds, quietly, in both directions. The practical test is whether someone new to the project could tell, in a minute, that it had been handled.

In practice

Numbers get quoted in meetings long after anyone remembers how they were calculated. Three things worth confirming about streaming data before you move on:

• Someone can say what the current setup is without going to look
• Streaming is worth it when the delay costs money — and you know whether that is true here
• There is a way to tell whether the last change to this helped

Most of the value here comes from doing the first two things, not all of them.