3 ms·

I've the feeling that when talking about Data Modeling, Redis really does not fit into the key-value category.

• ericmoritz 15y ago
  That's somewhat true. There's no need to model data structures like trees, maps, sets and lists in a data store that supports them natively. This article is still useful when using Redis because the article describes techniques apart from modeling fundamental data structures; most of the indexing techniques are still applicable to Redis, for instance. As an example, the Composite Key Index technique could be accomplished using a sorted set to store the ordered set of keys and Redis's k/v functionality to retrieve the values.
• eternalban 15y ago
  To the extent that one could talk about data modeling using the constructs of an imperative language e.g. C then one can do the same with Redis (with the caveat that Redis lacks a reference type). K/V only stores restrict the semantics to that of maps e.g. map["foo"]=bar, but if they introduce richer operations e.g. map-reduce on the K/V containers (e.g. map.apply(func)), then it is pretty much Redis restricted to its String type. I personally have a preference for unified views of systems so my bias is to look at the entire hierarchy of storage (image) and memory model (semantics) as a singular space, with back end disks as Ln to L1 cache on the CPU. In this light, to me Redis is a memory manager(/cache) + DSL, serving at Lx (where x is somewhere south of local Disk and north of a durable and consistent distributed FS backend e.g. HDFS).