AWS DynamoDB vs. MongoDB

NoSQL (non SQL) databases are the current standard for modern web applications involving big data. It has proven adept in storage and retrieval of various data structure types, whether the data is structured or not. Lacking the requirements of predefined schema, applications with NoSQL develop faster, allow modifications in real-time, and require minimal overhead. With ease of scaling, multiple industries have found widespread use.

MongoDB Benefits

MongoDB is incredibly flexible in how it can be deployed, including on-site and in the cloud. It has data validation rules and cloud monitoring that are incredibly suitable inside of a cloud-based web application.

MongoDB stands out with its extensive performance monitoring capabilities, allowing businesses to track and optimize their database performance closely. It also boasts the ability to scale horizontally across geographies, making it a reliable choice for mission-critical applications. MongoDB offers various versions with different characteristics. MongoDB Community Server is an open-source version that is freely available for anyone to use. On the other hand, MongoDB Enterprise Advanced Server is a self-service option, but it is not open-source. MongoDB Atlas provides a fully managed version of MongoDB accessible through popular cloud service providers like AWS, Azure, and Google Cloud.

This versatility makes it an ideal choice for businesses operating in multi-cloud environments, as they can seamlessly deploy and manage applications across different cloud providers.

The pricing structure for MongoDB on AWS offers a pay-as-you-go model for MongoDB Atlas usage. A free tier for beginners includes up to 5GB of storage of shared RAM and shared CPUs for use with the M0, M2, and M5 MongoDB cluster tiers. For shared instances on AWS, the pricing starts at $9 per month, while dedicated instances are priced at $60 per month for MongoDB Atlas utilization.

  • Supports automated sharding and horizontal scaling for optimal location of data. This is particularly beneficial for low-latency writes globally.
  • High-availability clusters allow for constant uptime with availability almost all the time for all cloud providers.
  • At least three data nodes per replica set are deployed by default across all AWS availability zones to help ensure accessibility and uptime.
  • Optimal for JSON format, especially in document databases.
  • Minimize latency since more complex queries are executed locally.
  • Extensive monitoring dashboard for keeping tabs on performance.

Amazon DynamoDB Benefits

DynamoDB is the AWS local solution, meaning the simplification of management and implementation as well as removing the need to physically upkeep servers. It is a key-value and document database, good for low-latency data access across industries such as retail, IoT, and various forms of entertainment media. It currently remains the biggest component in some of the biggest AWS customers’ applications, like Netflix and Nike.

Amazon DynamoDB shines for businesses that have already invested in or plan to adopt AWS as their cloud standard. Its native integration with AWS offers ease of deployment, automated management, and seamless integration with other AWS services. This means that updates are automated, reducing the burden on businesses, and allowing for optimized scaling that aligns with operational expenditure. By leveraging the automated scaling capabilities of AWS services, DynamoDB ensures resources are dynamically allocated to match workload demands, resulting in efficient performance and cost optimization.


  • Tables automatically replicate data to distribute the application globally across select access zones. This allows for read and write changes in milliseconds.
  • Like all other AWS services, it scales tables up and down to adjust for anticipated capacity and maintain performance.
  • Almost constant monthly uptime across each AWS region.
  • Capable of supporting 10+ trillion requests per day and 20+ million requests per second.
  • Capable of backing up millions of terabytes without negatively impacting performance.

Comparison Considerations


AWS NoSQL databases like MongoDB and DynamoDB offer businesses the opportunity to achieve better scalability and performance compared to traditional relational database models. By leveraging these powerful NoSQL databases, businesses can optimize their data management strategies and maximize operational efficiency.

When considering MongoDB, businesses can benefit from its extensive performance monitoring capabilities. This allows them to closely monitor and analyze the performance of their NoSQL-based applications, ensuring optimal functionality. Additionally, MongoDB’s ability to easily scale horizontally enables businesses to handle increasing amounts of data without sacrificing performance. What’s more, MongoDB is already compatible with popular cloud services such as Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP), making it a seamless choice for businesses operating in multi-cloud environments.

On the other hand, if a business is invested in AWS or planning to do so, DynamoDB emerges as the preferred NoSQL solution. Being native to AWS, DynamoDB offers automated updates and streamlined integration, reducing complexity and ensuring smooth operation. Its standard automated scaling feature, which is characteristic of AWS services, allows businesses to optimize costs and align them with operational expenditures effectively.

Regardless of which NoSQL solution appears to be more optimal for an application’s needs, such as MongoDB or DynamoDB, the decision ultimately depends on how the app itself is constructed. However, when businesses currently using MongoDB plan to migrate to AWS, Amazon offers a helpful solution called AWS Data Migration Service (AWS DMS). This service is designed to assist in the smooth transition of MongoDB databases to AWS, ensuring minimal downtime and successful migration. Every migration process is unique, and it is crucial to consider the design and data differences between the source (MongoDB) and target (AWS) databases, especially when dealing with complex scenarios like moving sharded MongoDB cluster data to DynamoDB tables. To ensure migration success and a seamless transition, it is highly recommended to seek the expertise of an AWS Consulting Partner. Their experience and knowledge can provide valuable insights and guidance throughout the migration process, ensuring that neither MongoDB nor DynamoDB is implemented poorly and that the migration to the cloud is carried out efficiently and effectively.

In conclusion, AWS NoSQL databases present businesses with the opportunity to enhance scalability and performance in managing their data. Whether it’s through MongoDB’s advanced monitoring capabilities and compatibility with various cloud services or DynamoDB’s seamless integration with AWS and automated scaling, businesses can leverage these NoSQL databases to meet their specific needs and achieve optimal results in their operations.

Dolan Cleary

Dolan Cleary

I am a recent graduate from the University of Wisconsin - Stout and am now working with AllCode as a web technician. Currently working within the marketing department.

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