MongoDB

It's an open-source document database and leading NoSQL database. MongoDB is written in C++. It's a cross-platform document-oriented database program. It's developed by MongoDB Inc. and licensed under the Server Side Public License (SSPL). MongoDB uses JSON-like documents with the schema. It began developing in 2007 as a component of a planned platform as a service product.

Redis

According to the official homepage, Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports various data structures such as Strings, Hashes, Lists, Sets, etc. It has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence. It provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster. Redis is written in ANSI C and works in most POSIX systems like Linux, *BSD, OS X without external dependencies. The Redis project began when Salvatore Sanfilippo, nicknamed antirez, the original developer of Redis, was trying to improve the scalability of his Italian startup, developing a real-time web log analyzer. It was developed in 2009.

Redis vs MongoDB

MongoDB automatically takes care of balancing data and load across a cluster, redistributing documents automatically, and routing user requests to the correct machines.
The data model available within MongoDB allows you to represent hierarchical relationships, to store arrays, and other more complex structures more easily.
MongoDB environments are very scalable. Companies across the world have defined clusters with some of them running 100+ nodes with around millions of documents within the database.
In MongoDB, each database contains collections which in turn contains documents. Each document can be different with a varying number of fields. The size and content of each document can be different from each other.
In MongoDB, the document structure is more in line with how developers construct their classes and objects in their respective programming languages.
With MongoDB, Developers will often say that their classes are not rows and columns but have a clear structure with key-value pairs.
MongoDB supports search by field, range queries, and regular expression searches. Queries can be made to return specific fields within documents.
MongoDB can provide high availability with replica sets. A replica set consists of two or more MongoDB instances. Each replica set member may act in the role of the primary or secondary replica at any time.
MongoDB uses the concept of sharding to scale horizontally by splitting data across multiple MongoDB instances.
MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure.
MongoDB provides horizontal scalability as part of its core functionality. Automatic sharding distributes data across a cluster of machines, while replica sets can provide eventually-consistent reads for low-latency deployments
Redis is fairly simple to set up, use and learn.
Redis excels a well-known caching solution. It isn’t a plain cache solution – it also has advanced data structures that provide many powerful ways to save and query data that can’t be achieved with a vanilla key-value cache.
Redis provides persistence that you can opt to set up, so cache warming in the event of a crash is hassle-free.
Redis doesn’t have inbuilt encryption on the wire. It isn’t a seamless, mature clustering solution. It can be a pain to deploy in large-scale cloud deployments with Redis.
Redis performs considerably better for reads for all sorts of workloads, and better for writes as workloads increase.
Redis is single-threaded, it (mostly) gets more done with running on one core than MongoDB does while saturating all the cores.
Redis, for non-trivial data sets, uses a lot more RAM compared to MongoDB to store the same amount of data.
For MongoDB, CPU was saturated by 32 threads onward. Greater than 300% usage with single-digit idle percentages. For Redis, at 128 threads, runs failed often with read-timeout exceptions.
For Redis, CPU utilization never crossed 95%. So, Redis was consistently performing better than MongoDB while running on a single thread, while MongoDB was saturating all the cores of the machine.
MongoDB has a single-master replication with built-in auto-election. This means you can have a second database set up and it can be auto-elected if the primary database becomes unavailable.
Redis offers master-slave replication. Using Redis Enterprise, you can have a cluster manager and shared-nothing cluster architecture.
MongoDB is better for prototyping and is helpful when you need to get data into a database and you’re not certain of the final design from the beginning.
For applications that need real-time data, Redis can be great because it can look up information about specific keys quickly.

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Redis vs MongoDB - which is better for your next project?