NoSQL databases have become more popular because of the need for more flexible backend solutions. These databases run applications that require a more flexible data structure than traditional structured databases can provide. Robust feature-rich NoSQL database platforms famous for NoSQL databases include MongoDB and DynamoDB.
This article guide will compare these two databases to help you choose the right one for your project.
Differences between MongoDB and DynamoDB
These two databases offer the same functions and feature sets; however, they differ through crucial factors. These factors are;
Data model and schema
DynamoDB offers a limited number of available data types, while single items are limited to 400KB. On the other hand, MongoDB uses the BSON format to store its data in documents with support for a greater variety of data. These varieties of data range from strings timestamps to different integers and decimal types. MongoDB supports document sizes up to 16MB, and this limit can be extended by breaking down data into multiple documents using GridFS.
DynamoDB is not directly connected to the internet since requests are routed through an API gateway where AWS manages the authorization. In MongoDB, users are responsible for most of the security practices. These practices range from managing access, routing traffic and firewalls, etc.
Backup and recovery
MongoDB Atlas supports continuous and on-demand cloud backups, although it requires more configurations than DynamoDB to get everything properly configured. On the other hand, DynamoDB offers Multi-region and Multi-AZ data replication out of the box as part of the AWS service. This supports both on-demand and automated backups with point-in-time recovery.
Data query and indexes
MongoDB is more flexible in querying data as it allows users to aggregate and query data locally in many ways, such as:
- Single keys
- Graph traversals
- JOINs etc.
On the other hand, DynamoDB locally supports only Key-value queries yet enables users to do complex aggregations using other AWS services, i.e., Amazon Redshift. The problem with using different services is increasing cost, latency, and complexity.
MongoDB supports different indexing types such as compound TTL, hash, wildcard, text, array, etc.… and the indexes are strongly consistent with the underlying data, while DynamoDB supports two types of secondary index. These indexes are the Global Secondary Index (GSI) and Local Secondary Index (LSI).
Deployment environment and strategy
The most notable difference between these two databases is that MongoDB is platform-agnostic while DynamoDB is limited to AWS. This means that with Mongo DB, a user can configure the database to run anywhere from the user’s local machine or on-premise deployment to any cloud provider. On the other hand, DynamoDB only allows users to configure and use it through AWS, even though it offers a downloadable version for testing and development.
Choosing between MongoDB and DynamoDB
Choosing the suitable database depends on multiple factors such as:
- Storage requirements
- User requirements etc.
MongoDB and DynamoDB can’t be compared directly since they target different use cases. For example, DynamoDB is a managed NoSQL database service, while MongoDB is NoSQL database software. MongoDB Atlas is the only edition of MongoDB that can be directly compared to Dynamo DB.
DynamoDB offers the best in the following areas if you are using the AWS echo system to deploy and manage applications:
- Ease of use
The only major downside with DynamoDB is vendor locking users without changing the deployment environment quickly. Meanwhile, MongoDB Atlas frees users to use any supported cloud provider to create MongoDB database clusters and Move to an on-premise MongoDB database with minimal configurations.
In this argument, MongoDB has the edge over DynamoDB because its features are set for managing the underlying dataset with native schema validations, multiple index type support, etc. A user can configure it to cater to meet database needs.
MongoDB and DynamoDB are both solid databases that support various user needs. However, a user needs to consider when selecting the best option carefully. This article has expounded on these two databases, and we hope that it helps in choosing between them. In case of any problem, you can write to us in the comment section, and we will get back to you.