Historically, we have used Redis in two ways at GitHub:
We used it as an LRU cache to conveniently store the results of expensive computations over data originally persisted in Git repositories or MySQL. We call this transient Redis.
We also enabled persistence, which gave us durability guarantees over data that was not stored anywhere else. We used it to store a wide range of values: from sparse data with high read/write ratios, like configuration settings, counters, or quality metrics, to very dynamic information powering core features like spam analysis. We call this persistent Redis.
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