DynamoDB vs MongoDB: Which one to choose and why?

DynamoDB vs MongoDB: Which one to choose and why?

While developing an app, one of the main pain points that we face is picking up a database. Developers often debate the merits of using SQL vs NoSQL, on one hand, you have safety, security, and consistency and on the other, you have productivity, scalability, and flexibility. DynamoDB vs MongoDB is some of the big database giants in the market. In this article, we’ll look at what these NoSQL databases offer and select the database that suits you best.

Why NoSQL?👀

The problem with relational database management systems(RDBMS) like MySQL is that these are not easily scalable and they require a lot of computing and memory power. So, they are great for storing small amounts of data but as the company grows, handling the data becomes problematic. SQL DBs are good for vertical scalability but NoSQL DBs are great for vertical and horizontal scalability. Think of vertical scalability as adding more floors to an existing building, whereas horizontal scaling means adding more buildings.

NoSQL databases are essentially the exact opposite of SQL and you don’t need to worry about relational data. The best thing is, you can insert any form of data needless of its fabric. In NoSQL, every item in the database stands on its own. The key field stores a unique identifier value and the value field contains the full description of an entity. This simple design makes NoSQL databases scale better. Almost all big tech companies use NoSQL databases to store their data.

NoSQL paradigms

  • Key-Data
  • Wide-Column
  • Graph
  • Document

DyanamoDB and MongoDB are both document-oriented(explained later) databases. Let’s understand each of these databases thoroughly.


MongoDB is one of the most advanced and popular NoSQL databases out there. It was developed and released in 2009 by MongoDB Inc. A funny thing about MongoDB is that its name, Mongo comes from Humongous. MongoDB is a record-oriented database. This means that the data is stored in the form of JSON-like documents which are organized into collections where the data can be queried.

JSON(JavaScript Object Notation) is structured as objects containing key-value pairs with a format something like this:

{ "key" : "value", "id" : 2134, "firstname" : "Marty", "email" : ["marty@gmail.com"], "phone" : ["123-456", "456-789"] }
Code language: JavaScript (javascript)

You can see that while having multiple values, we can define these values in the form of arrays. A single document stores all the data for each record instead of storing it in different tables. The schemas in MongoDB are very flexible and there are no rules for storing the data. You can store any kind of data in any document. Also, the scaling in MongoDB is very cost-effective and as seen earlier, instead of vertical scaling only, MongoDB provides both vertical and horizontal scaling. Because of the structure, this type of database is very efficient, easy to understand, and easy to modify and update. You can learn more about MongoDB deployment on MongoDB documentation.

MongoDB provides a community edition for developers that you can download and use its services for free. But with that, you’ll have to take care of the system maintenance, updates, and management all by yourself.

MongoDB Atlas

MongoDB also provides an alternative if you don’t want to manage the server all on your own. Atlas provides a global cloud database service for modern applications. With Atlas, you can deploy a full-fledged server across AWS, Google Cloud, and Microsoft Azure that provides great security and scalability.

Now let’s have a look at the features of DynamoDB.


Amazon DynamoDB as mentioned earlier is also a NoSQL database that has been in the market for almost 10 years now. But, the idea of DynamoDB originated way back in 2004 when a company was facing scalability issues. DynamoDB is great for companies having large volumes of data flow that require fast performance. It also uses a record-oriented JSON format for storing data.

DynamoDB is highly flexible and is suited for heavy applications. It is always stored on the SSD(Solid state drive) storage for faster loading time. It also provides good security through AWS identity. DynamoDB is used in gaming industries and advertising technology.

DynamoDB vs MongoDB💥

Let’s look at some of the key differences the databases have from each other.

Platform Dependency

MongoDB is platform-independent and can be run on any device, be it a laptop or a mainframe computer. You can use any cloud provider of your choice to bring your app into action. Being platform-independent, it becomes easy for you to deploy the application with the server of your choice.

With DynamoDB, you are confined to the AWS ecosystem which is a construct for most people. It does not support any external cloud platform like Azure. So, DynamoDB is confined to AWS and does not give options to the users for choosing any other platform.


DynamoDB comes with good security support that is managed by AWS. This enables the user to access the server securely. The requests can be routed through a secured and authorized API gateway provided by AWS. MongoDB is also highly secured but it does not provide any out-of-the-box security features.

Supported Data Format

In terms of storing data, MongoDB is the clear winner as documents of large sizes can be stored in MongoDB.MongoDB stores sizes of up to 16,000 KB. Data of any format can be stored in MongoDB.

DynamoDB provides less storage capacity in comparison to its contender. Only some selected types of data types can be stored in DynamoDB.

Data Backup

MongoDB comes with full-fledged backup support for system failure. It also provides a snapshot and queryable backup that lets you access the data without restoring it.

DynamoDB only provides on-demand backup and does not provide a snapshot and queryable backup and in case of any failure, the data has to be recreated again.

Use of Index

Indexing is the bread and butter of performant databases. MongoDB does not charge for indexing data. It also supports mutual indexes that allow the document’s structure to be changed dynamically.

DynamoDB provides limited indexing. Indexing data in DynamoDB is much more complicated compared to MongoDB.

Data Integrity

Data is highly consistent and easy to maintain in MongoDB as it allows the user to see current data. Each transaction in MongoDB follows the ACID(Atomicity, Consistency, Integrity, and Durability) properties. Data integrity is not as good as MongoDB. Also, the ACID transactions are applied to limited operations making them vulnerable to external threats.

Quick Overview- DynamoDB vs MongoDB⚖️

DynamoDB is confined to the AWS ecosystem and cannot be used with any other cloud.MongoDB is platform-independent and can be deployed on any cloud.
Comes with highly secured out-of-the-box security.Secured but the community version is not much secure.
Stores small data size of only up to 400KB.Larger data sizes of up to 16,000 KB can be stored.
Does not support snapshot backup.Comes with snapshot backup support.
Data indexing is not free of cost.Data indexing is free of cost.
Pricing is expensive compared to MongoDB.Pricing is comparatively low and services offered are better than DynamoDB.
DynamoDB vs MongoDB


It is pretty obvious from the differences that MongoDB has an upper hand in this battle. From indexing to scaling, MongoDB is better in almost every aspect. Though DynamoDB is not an inferior database solution, it is meant for people who are invested in the AWS ecosystem.


Choosing the right database becomes an important part of your application and depending on the project you are working on, you might choose one over the other.

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