So lets consider one use case. We have a website where people login and we create a session to track that user across different pages on the website. Now the session will have data like user name (to display on the website), the user's location or IP address, the user's preferences, etc. So whilst the browser and the website communicate with a cookie (to identify this session), we need to store this session data somewhere. You can use a file or a database to read and write to this session data which works fine. But redis shines in this example where the speed is very good and you also have the session id as they 'key' and the session data as the 'value' that you can store.
Redis gives you amazing speed and because it provides a kv interface, the work is very easy.
Thanks, I never heard a practical example like this. I assume the "value" side of Key:Value can be a giant heap of JSON? So theoretically you can retrieve an entire collection of structured data as long as you know the key, correct?
And where the usefulness of K:V store is beaten by SQL is the point you would want to run a "JOIN" or "GROUP" on the data, for example if you wanted to count the number of keys containing a certain data point, correct?
Yes the big bag of data which is generally the value in the kv store is a json (either as a serialized string or a map if it is natively supported by redis).
Yes, the usefulness of SQL always is the join or group but with something like session, the idea is to just use it to dump values into the store which you don't want to reach into the database every time. So different teams will want to put in their own keys and data into the session object which means your DB session store becomes extremely difficult to maintain over time.
On the other hand, the joins and groups based on this can be handled later in time than in the req-response cycle itself.
Redis gives you amazing speed and because it provides a kv interface, the work is very easy.