if you want to build realtime applications then you need to write async functions in node that support in-mem data stores like redis. Although, mostly people are confused on why do we even need redis when we are using something like mongodb ?
The fundamentals can be broken down into :
Data Model :
Document oriented, JSON-like. Each document has unique key within a collection. Documents are heterogenous.
Key-value, values are:
- Lists of strings
- Sets of strings (collections of non-repeating unsorted elements)
- Sorted sets of strings (collections of non-repeating elements ordered by a floating-point number called score)
- Hashes where keys are strings and values are either strings or integers.
Disk, memory-mapped files, index should fit in RAM.
By key, by any value in document (indexing possible), Map/Reduce.
Both can be used for good results (Craig-list uses it).
MongoDB is interesting for persistent, document oriented, data indexed in various ways. Redis is more interesting for volatile data, or latency sensitive semi-persistent data.
- Redis can be used for user sessions and MongoDB can be used for user data.
- Redis can be used for advanced features (low latency, item expiration, queues, pub/sub, atomic blocks, etc …) on top of MongoDB.
#Please note you should never run a Redis and MongoDB server on the same machine. MongoDB memory is designed to be swapped out, Redis is not. If MongoDB triggers some swapping activity, the performance of Redis will be catastrophic. They should be isolated on different nodes.
On a higher level :
- Redis is often used as a caching layer or shared whiteboard for distributed computation.
- MongoDB is often used as a swap-out replacement for traditional SQL databases.
- Redis is an in-memory db with disk persistence (the whole db needs to fit in RAM).
- MongoDB is a disk-backed db which only needs enough RAM for the indexes.
There is some overlap, but it is extremely common to use both. Here’s why:
- MongoDB can store more data cheaper.
- Redis is faster for the entire dataset.
- MongoDB’s culture is “store it all, figure out access patterns later”
- Redis’s culture is “carefully consider how you’ll access data, then store”
- Both have open source tools that depend on them, many of which are used together.