Which database is best? A comparison of MongoDB vs. DynamoDB

Our comparison of MongoDB vs. DynamoDB revealed striking differences in each solution’s approach to storing and managing data. Above all, DynamoDB is fully embedded in the AWS cosmos. MongoDB on the other hand, could offer more freedom.

MongoDB vs. DynamoDB, two recommended NoSQL services

While in the past there was hardly any way around the classic SQL database, the emergence of ever larger amounts of data has meant that applications and websites need a new way of handling data. The solution came in the form of NoSQL systems (Not only SQL) such as MongoDB and DynamoDB. These do not work relationally thus making them much more flexible and, above all, more scalable. Instead of tables, these solutions mainly rely on documents. So, they can also store unstructured or semi-structured data in a way that creates clarity and saves space. If a company’s requirements grow, the database grows with them without any problems arising.

What is MongoDB?

MongoDB was released in 2009 by 10gen (now MongoDB, Inc.). It has since become one of the most popular solutions in the field of SQL database management systems. The software is written in C++ and stores data in the form of binary JSON documents (BSON). MongoDB is open source, distributed under the Server Side Public License (SSPL) and offers optional commercial support packages. The database, which owes its name to the English term “humongous” (meaning “gigantic”), is known for its flexibility and scalability. MongoDB uses the MongoDB Query Language (MQL) for queries.

What is DynamoDB?

DynamoDB has been around since 2012. The serverless NoSQL database comes from Amazon and is provided by AWS (Amazon Web Services) as a completely managed service. The application is proprietary and was originally written in Java to manage the ever-increasing volumes of data from the company’s own e-commerce activities. The database is document-oriented and is considered one of the fastest and most scalable solutions in the NoSQL segment. Although DynamoDB also uses tables, these are not relational. Due to its structure, the system is not only particularly suitable for large companies, but also for smaller companies whose data volumes and workloads increase over time.

The purpose and scalability of MongoDB and DynamoDB

On comparing the MongoDB and DynamoDB systems, it seems clear why the two NoSQL databases are used for similar purposes. The two systems can be used wherever large amounts of data need to be clearly stored and managed. MongoDB uses a technique called sharding for horizontal scaling. Large data records are automatically split and the load is distributed across several servers. As the system can also work with unstructured data without any problems arising, it is ideal for managing and providing websites and e-commerce applications. All required content, including images or videos, is stored in one document. Retrieval then takes place immediately without any noticeable operational delays.

DynamoDB offers similar deployment options. Amazon itself recommends the in-house database for applications, media workloads, e-commerce and gaming platforms, among others. This claim is pretty understandable since the system offers — at least theoretically — infinite scaling options and has nothing to hide when compared with MongoDB.

However, one of the biggest differences between the two systems is their integration into AWS. DynamoDB does not work outside of this ecosystem and is therefore only suitable for users who can live and work with this limitation. But in return, you get comprehensive administration and benefit from extremely fast read and write processes, even with rapidly increasing data volumes.

Functionality

Although both databases may have similar goals, a closer look at the MongoDB vs. DynamoDB comparison quickly reveals the different approaches. MongoDB completely does away with the SQL-typical tables and instead stores data in documents, which in turn are bundled into collections. These documents in BSON format consist of key-value pairs, can have different schemas and can be changed by adding or deleting a field. While keys always consist of character strings, values can also contain character strings, other documents, arrays or Boolean values. The text search in MongoDB is carried out via a text index.

DynamoDB works as a NoSQL key-value store that stores data on SSD hard disks. The data can be stored schema-free as numerical values, strings or binary. The information is divided into non-relational tables consisting of items that must contain at least one attribute. The operations “Create”, “Read”, “Update” and “Delete” are available for writing and reading.

Data structure

There are also differences in the comparison of MongoDB vs. DynamoDB with regard to the data structure and maximum data size. MongoDB’s storage format is called BSON and is a binary form of JavaScript Object Notation (JSON) that does not require a schema. If you want to create a new document, you do not need to create your own collection in advance. Instead, you create the document with a simple command, which is then either inserted into an existing collection or created automatically. The system allows data with a maximum size of 16 MB.

The data structure of DynamoDB, on the other hand, is much more reminiscent of the table form of classic SQL solutions. Here, too, there are tables that contain elements with certain properties, although the number of these properties may vary. Before you can use a table, you must first create it and define a primary key that partitions the data. Each of these partitions contains three nodes with a copy of the data. As the database is completely managed by the system, this process is fully automated. There is also a noticeable difference between MongoDB and DynamoDB in the size of the stored documents. With Amazon’s service, the limit is maximum 400 KB.

Availability of the data

By default, DynamoDB divides the three nodes mentioned into one primary node (leader node) and two subordinate nodes. All read and write operations are performed on the primary node first. Only then is the replication carried out on the two subordinate nodes. However, it is also possible to distribute the read operations to all three nodes in order to prevent performance losses.

The somewhat older solution in the MongoDB vs. DynamoDB comparison also distributes the data across several nodes and thus prevents problems which could be caused by a server failure. Similar to the competition from Amazon, there is a primary node that receives the write operations and then makes the data available to the subordinate nodes. If the main node fails, one of the other nodes automatically takes its place and becomes the lead node, which, thanks to replication, already contains all of the data. The process can take up to 60 seconds.

Infrastructure, compatibility and programming languages

One of the clearest differences between MongoDB and DynamoDB is the deployment and infrastructure of the two services. MongoDB is a completely free open source solution with proprietary support offerings. The database management system is compatible with most cloud solutions, operating systems and containers. How much control and administrative effort is necessary and possible is entirely up to the user. The database must be configured and maintained independently. On the one hand, this can be demanding and time-consuming. On the other, it can offer a great deal of freedom.

DynamoDB takes a different approach. The database is part of the AWS ecosystem and does not work outside of this environment. This means that although DynamoDB works extremely well with other tools from Amazon, the application is only compatible with other solutions to a limited extent. The fully managed database is immediately ready for use and handles updates, scaling and other tasks automatically. This does mean that users only have limited insight into the work “behind the scenes”.

The following table summarizes which programming languages the two systems support:

Security

DynamoDB performs a number of tasks for its users, including all security activities. As part of the AWS cosmos and the IAM model (Identity and Access Management), the database is well protected and embedded. There is no direct connection to the internet, as requests are first routed through an API gateway.

Compared to DynamoDB, the workload when using MongoDB is significantly higher if you want to ensure the security of your database. Access authorizations, roles and firewalls must be implemented and maintained independently, at least in the standard versions of the system. Managed solutions that provide all the necessary security features can resolve this issue.

Which companies rely on MongoDB and DynamoDB?

Companies that use MongoDB in whole or in part include the following:

• Adobe
• Amadeus
• AppScale
• Craftbase
• Disney
• Etsy
• Foursquare
• Lyft
• MTV
• The New York Times
• Via Varejo

Companies and platforms that manage their data with DynamoDB include the following:

• Airbnb
• Amazon
• Comcast
• Disney
• Dropbox
• Netflix
• Nike
• Redfin
• Samsung
• Tinder
• Zoom

Which service suits your requirements?

MongoDB and DynamoDB are two very powerful database management systems that remain flexible and scalable thanks to their NoSQL approach. However, the approach of the two solutions differs from each other. If you are looking for a system that is perfectly embedded in the AWS cosmos, has a strong security architecture and takes care of most administrative tasks for you, DynamoDB is an excellent choice. If, on the other hand, you want freedom of choice in terms of your cloud environments and configuration, MongoDB is the optimal service.