The Differences Between MongoDB vs Redis (Pros and Cons)

The importance of data in today’s world can hardly be overstated. Every upcoming significant technological advancement is being fueled by the abundant data collected through various mediums. In such a time, the conversation around data storage is an important one. After all, efficient storage is crucial for the effective use of data.

For the longest time, relational databases were the go-to option for all kinds of data storage, queried by the popular SQL. However, performance challenges brought on by increasing volumes of data lead technologists to devise new storage strategies. The birth of NoSQL databases gave users the opportunity to opt for better-performing data storage options.

While there are many NoSQL options available, choosing between the popular ones can be confusing for some users. This article will go through two in-demand NoSQL databases, MongoDB and Redis, and compare both with each other. It will give a flavor of what main advantages each NoSQL database offers and some of its drawbacks.

Differences Between MongoDB and Redis

A Document-Based Database With MongoDB

MongoDB is a NoSQL database that employs a document-based model. Each document stores data in the JSON-like key-value pair format. There is no relational schema in such a system, and the set of fields and their data type can change between multiple documents in a collection. However, you can also set the documents to have a similar structure and enforce data validation rules as well.

The documents your database is built on are saved on a cluster of servers. MongoDB’s distributed architecture enables facilities like high availability and geographic distribution. Through the MongoDB Server product, you can access and run your database from wherever you want. Such facilities make MongoDB a popular database choice when setting up a cloud computing environment, like AWS or Azure, as shown in our article on how to install MongoDB on AWS, on our blog.

Apart from data storage, MongoDB also provides powerful facilities to analyze and process the stored data. It supports analysis techniques like ad-hoc queries and real-time aggregation directly in its environment. MongoDB is one of the most popular NoSQL databases currently on the market. While mainly open-source, it also offers a commercial enterprise-level version under its Atlas product.

NoSQL Databases

A Data Structure Driven Approach With Redis

Redis is another hugely popular open-source NoSQL database. Like MongoDB, it also avoids setting up data schemas and stores data in a key-value pair. However, Redis takes a different approach to storing data by employing five different types of data types for its values. Unlike MongoDB, it doesn’t use a document-based model but persistent disk storage.

Redis uses different techniques to provide data retrieval several hundred times faster than your regular SQL queries. Its performance utilizes replication to scale read performance and ‘client-side shading’ to scale write performance. The data structures Redis uses include standards like strings, lists, and hashes, along with unique ones like sets and ‘zsets’. Each of these has dedicated and shared commands used for querying and updating.

The main aim of Redis is to provide a fast in-memory storage solution that can be used as a database and a cache as well. However, it also promises speed with scale. Being an open-source project, Redis enjoys an active and dedicated developer community.

The speed of Redis makes it a much-preferred option in the case of real-time analytics, geospatial, chat applications, and even machine learning. The popularity of Redis for its speed and scalability has led to many popular cloud computing environments offering it as a database option, as shown in our article on how to setup Redis on AWS, on our blog.

MongoDB vs Redis: The Pros & Cons

Having gone through the main features of MongoDB and Redis, it is vital to highlight the main advantages and drawbacks of both databases. Given below are some of the main aspects in which they stand out and in which they don’t.



  1. MongoDB sports a significantly fast query performance by storing most of the data on the RAM. It is much quicker than on-disk storage but requires more RAM space for large volumes of data.
  2. MongoDB’s query language is expressive and straightforward in nature. The simplicity and directness of its NoSQL-based query language are some of the main reasons that the NoSQL approach has found appreciation among developers. 
  3. MongoDB offers horizontal scalability instead of the regular vertical scalability of relational databases. It employs a technique called ‘native sharding’, which basically means spreading data across multiple machines.
  4. MongoDB offers a ‘fully elastic’ database as a service (DBaaS) for small-level developers and enterprises as well. The DBaaS comes with end-to-end security measures in place.


  1. As the documents in a MongoDB database store the field names along with the values, the data size is significantly larger than regular databases with fixed schemas. Each document can have a size of up to 16 MB, although not more than that.
  2. There is no support for joins in MongoDB, which is a reasonably basic facility offered in databases. Without joins, MongoDB databases can be prone to data redundancy.
  3. While MongoDB recently started supporting transactions through their transaction API, resulting in performance costs for single document writes. The API comes with other limitations as well, making it a hassle to use in some cases.



  1. It is one of the fastest caching technologies on the market. Its throughput is often limited by the available network strength or size and then the processor size.
  2. Its flexible data structures support all different kinds of data storage scenarios. Each key-value pair can save up to 512 MB of data, giving a chance to save enormous data in just one object.
  3. Redis has its own hashing technique that is used to boost read and write performance significantly. However, it is dependent on factors like available RAM size on Redis and the number of objects you want to store.
  4. Redis supports asynchronous replication because of its low latency and high performance. It also supports a dedicated WAIT command that is used to induce synchronous replication.


  1. Redis is essentially a data structure server. It supports commands and doesn’t support a query language, so there is no case of using ad-hoc queries. Data access paths have to be designed, and this results in a loss of flexibility.
  2. The security offered by Redis is pretty basic. It only provides data access rights.
  3. To achieve scalability, Redis requires setting up and deploying multiple instances of itself. However, the enterprise-level product of Redis promises easy scalability and support for sharding as well.

The Final Choice: MongoDB or Redis?

The choice of the data storage facility can make all the difference for an enterprise and its day-to-day operations. When choosing the database, it is important to review the requirements and focus on the crucial operations. For some enterprises, storing large volumes of data is important while speedy data retrieval is crucial for others. The final choice of the database rests on such factors.

In the case of MongoDB vs. Redis, both are fairly popular NoSQL database choices. As we saw, MongoDB finds its strengths in scale and query performance, while Redis offers lightning-fast commands and caching. Both are wonderful NoSQL options and should be chosen based on your requirements as needed. 

Avatar for Emad Bin Abid
Emad Bin Abid

I'm a software engineer who has a bright vision and a strong interest in designing and engineering software solutions. I readily understand that in today's agile world the development process has to be rapid, reusable, and scalable; hence it is extremely important to develop solutions that are well-designed and embody a well-thought-of architecture as the baseline. Apart from designing and developing business solutions, I'm a content writer who loves to document technical learnings and experiences so that peers in the same industry can also benefit from them.

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