Redis stores keys pointing to values. Keys can be any binary value up to a reasonable size (using short ASCII strings is recommended for readability and debugging purposes). Values are one of five native Redis data types.
1.strings a sequence of binary safe bytes up to 512 MB
2.hashes a collection of key value pairs
3.lists an in-insertion-order collection of strings
4.sets a collection of unique strings with no ordering
5.sorted sets a collection of unique strings ordered by user defined scoring
A Redis string is a sequence of bytes.
Strings in Redis are binary safe (meaning they have a known length not determined by any special terminating characters), so you can store anything up to 512 megabytes in one string.
Strings are the cannonical "key value store" concept. You have a key pointing to a value, where both key and value are text or binary strings.
A Redis hash is a collection of key value pairs.
A Redis hash holds many key value pairs, where each key and value is a string. Redis hashes do not support complex values directly (meaning, you can't have a hash field have a value of a list or set or another hash), but you can use hash fields to point to other top level complex values. The only special operation you can perform on hash field values is atomic increment/decrement of numeric contents.
You can think of a Redis hashes in two ways: as a direct object representation and as a way to store many small values compactly.
Direct object representations are simple to understand. Objects have a name (the key of the hash) and a collection of internal keys with values. See the example below for, well, an example.
Storing many small values using a hash is a clever Redis massive data storage technique. When a hash has a small number of fields (~100), Redis optimizes the storage and access efficency of the entire hash. Redis's small hash storage optimization raises an interesting behavior: it's more efficient to have 100 hashes each with 100 internal keys and values rather than having 10,000 top level keys pointing to string values. Using Redis hashes to optimize your data storage this way does require additional programming overhead for tracking where data ends up, but if your data storage is primarly string based, you can save a lot of memory overhead using this one weird trick.
You can insert to, delete from, and traverse lists from either the head or tail of a list.
Use lists when you need to maintain values in the order they were inserted. (Redis does give you the option to insert into any arbitrary list position if you need to, but your insertion performance will degrade if you insert far from your start position.)
Redis lists are often used as producer/consumer queues. Insert items into a list then pop items from the list. What happens if your consumers try to pop from a list with no elements? You can ask Redis to wait for an element to appear and return it to you immediately when it gets added. This turns Redis into a real time message queue/event/job/task/notification system.
You can atomically remove elements off either end of a list, enabling any list to be treated as a stack or a queue.
You can also maintain fixed-length lists (capped collections) by trimming your list to a specific size after every insertion.
A Redis set contains unique unordered Redis strings where each string only exists once per set. If you add the same element ten times to a set, it will only show up once. Sets are great for lazily ensuring something exists at least once without worrying about duplicate elements accumulating and wasting space. You can add the same string as many times as you like without needing to check if it already exists.
Sets are fast for membership checking, insertion, and deletion of members in the set.
Sets have efficient set operations, as you would expect. You can take the union, intersection, and difference of multiple sets at once. Results can either be returned to the caller or results can be stored in a new set for later usage.
Sets have constant time access for membership checks (unlike lists), and Redis even has convenient random member removal and returning ("pop a random element from the set") or random member returning without replacement ("give me 30 random-ish unique users") or with replacement ("give me 7 cards, but after each selection, put the card back so it can potentially be sampled again").
Redis sorted sets are sets with a user-defined ordering.
For simplicity, you can think of a sorted set as a binary tree with unique elements. (Redis sorted sets are actually skip lists.) The sort order of elements is defined by each element's score.
Sorted sets are still sets. Elements may only appear once in a set. An element, for uniqueness purposes, is defined by its string contents. Inserting element "apple" with sorting score 3, then inserting element "apple" with sorting score 500 results in one element "apple" with sorting score 500 in your sorted set. Sets are only unique based on Data, not based on (Score, Data) pairs.
Make sure your data model relies on the string contents and not the element's score for uniqueness. Scores are allowed to be repeated (or even zero), but, one last time, set elements can only exist once per sorted set. For example, if you try to store the history of every user login as a sorted set by making the score the epoch of the login and the value the user id, you will end up storing only the last login epoch for all your users. Your set would grow to size of your userbase and not your desired size of userbase * logins.
Elements are added to your set with scores. You can update the score of any element at any time, just add the element again with a new score. Scores are represented by floating point doubles, so you can specify granularity of high precision timestamps if needed. Multiple elements may have the same score.
You can retrieve elements in a few different ways. Since everything is sorted, you can ask for elements starting at the lowest scores. You can ask for elements starting at the highest scores ("in reverse"). You can ask for elements by their sort score either in natural or reverse order.
For all possible operations on sorted sets, see the sorted sets docs.