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One difference between the two is that a system process is aggregated, which means it contains a inventory of all elementary flows combined for the preceding life-cycle stages = life-cycle inventory (LCI). So there's no need for providers, it's all in there.

On the other hand unit processes contain product flows that can be and should be tracked back to other processes or providers.

Which means using system processes results in smaller product systems with less links and thus shorter computation time / less CPU / less RAM usage but you loose detail as you cannot track back where your impacts coming from.

Also, a database containing only system processes is usually 10-20x bigger in size than the same database with only unit processes.
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"Also, a database containing only system processes is usually 10-20x bigger in size than the same database with only unit processes."

That is surprising. Shouldn't unit process database be bigger than the database with system processes? Why is that an aggregated database requires more memory than unit process database?

PS: I edited the original question.
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This topic reminds me to classic CPU vs. RAM tradeoff in image compression: you either work with less compression so you need less CPU but more RAM, or vice versa, you work with more compression that requires more CPU but results in smaller storage footprint.
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Okay. I see. Since all calculations have been done before hand, you need more storage in systems process but less computation. In Unit process, you do all calculations "on the fly", so you need more RAM, but less hard disk storage. Is it right?
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