Category: Data

Redis Labs sponsored this post. You have a fancy data pipeline with lots of different systems.

The more systems you use, the more places you are duplicating your data and the more chances of it going out of sync or stale.

In our case, you have the data in some form or quantity, and you need to transform it before we can use it.

We compared four systems in this example and found out that Case 3 or Case 4 are the simplest with an IMS of 1.

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