DynamoDB vs MongoDB

What is DynamoDB?

DynamoDB is Amazon's own NoSQL database that supports key-value and document data provided through Amazon Web Services. With DynamoDB, you can reduce the administrative burden of running and scaling distributed databases, so you don't have to worry about hardware provisioning, setup, and configuration, replication, software patches, or cluster scaling.

DynamoDB offers limited storage, and always-free DB instances to AWS users using their AWS Free Tier for testing and development.

What is MongoDB?

MongoDB is an open-source document-oriented database designed to store large amounts of data and also allows you to work with that data very efficiently. MongoDB uses collections and documents instead of using tables and rows as in traditional relational databases. Documents consist of key-value pairs which are the basic unit of data in MongoDB. Collections containing tuples and a function equivalent to relational database tables.

The MongoDB database is developed and maintained by MongoDB.Inc under the SSPL (Server Side Public License) and was originally released in February 2009.

DynamoDB Vs MongoDB: Differences

Infrastructure

DynamoDB is a fully managed solution provided by Amazon via Amazon Web Services (AWS), whereas MongoDB is an open-source product. While DynamoDB is only available as part of AWS, with DynamoDB you don't have to worry about provisioning, monitoring, and running servers. On the other hand, with MongoDB, you can configure your database to run virtually anywhere— from your local machine, container, or on-premises deployment to any cloud service provider.

Security

When it comes to security, DynamoDB offers much better features as its service is managed by AWS. The security model is based on Identity and Access Management (IAM), enabling secure management of access to AWS services and resources.

DynamoDB is not directly accessible from the Internet, which adds another layer of security on top of its specific configuration.

MongoDB also offers good security features, but the default configuration does not. To increase security, users need to make more configurations after the installation.

Data Types

DynamoDB supports many different data types for table attributes. Each data type can be classified as follows:

Scalar − Scalar type represents a single value, and includes number, string, binary, Boolean, and null.

Document − A Document type represents a complex structure possessing nested attributes, and includes lists and maps.

Set − Set type represents multiple scalars and includes string sets, number sets, and binary sets.

MongoDB supports many different data types: String, Integer, Boolean, Double, Arrays, Timestamp, Object, Null, Symbol, Date, Object ID, and Binary data.

Database Structure/ Schema

MongoDB uses the BSON format to store its data in documents and schema-free databases. On the other hand, DynamoDB databases have tables containing items that in turn have attributes. Items in the table can have different numbers of attributes.

MongoDB supports document sizes up to 16MB, while in DynamoDB single items are limited to 400KB(If you need to store large objects using DynamoDB, AWS recommends using another service, such as S3). But both databases support ACID transactions.

Querying Data

DynamoDB natively only supports key-value queries while allowing users to perform aggregations and more complex query types using other additional AWS services, such as Amazon Redshift and Elastic MapReduce.

MongoDB provides more flexibility in querying data as it allows users to aggregate and query data natively in many ways such as; single key, graph traversal, geospatial queries, extents, facet search, and more.

Indexes

DynamoDB uses indexes for primary key attributes to improve access. DynamoDB supports two types of secondary indexes:

Global secondary index - An index with a partition key and a sort key that can be different from those on the base table. A global secondary index is considered "global" because queries on the index can span all of the data in the base table, across all partitions. [2]

Local secondary index - An index with the same partition key as the base table, but a different sort key. A local secondary index is "local" in the sense that every partition of a local secondary index is scoped to a base table partition that has the same partition key value. [2]

MongoDB supports creating indexes for any field in a document with support for secondary indexes. The structure of the document can be changed without having to update the collection schema on the backend.

Database Backup and Distribution

DynamoDB supports Multi-AZ and Multi-Region data replication as part of AWS services. This supports on-demand and automatic (continuous) backups. MongoDB can support multi-node clusters, but setting it up can be challenging. Additionally, the developer is responsible for all backup and recovery tasks in on-premises or manual MongoDB deployments.

MongoDB or DynamoDB

If you are already working with AWS and your business relies on it. Then, DynamoDB is probably the best option for you. As it will be easy to integrate it with the current infrastructure. On the other hand, if you want hybrid-cloud infrastructure, then MongoDB is more suitable for you as MongoDB is a transparent open-source solution that you can run anywhere.

Both MongoDB and DynamoDB are robust NoSQL databases that support the needs of different users. However, their effectiveness depends on different factors such as speed, complexity, user requirements, storage requirements, and more. When it comes to deciding which one to use, it’s not a simple choice. With all the differences which we have seen above, it’s not about selecting the better one among the two, rather it’s all about which one provides the best feature for your use cases. In the end, the one best suitable for your use cases wins the race.