DynamoDB and MongoDB are two of the most popular NoSQL databases on the market. But which one should you choose for your project? In this article, we’ll compare and contrast these two databases in terms of features, performance, scalability, and more.
But How Do You Choose Between DynamoDB and MongoDB?
If you’re a small team bootstrapping a proof-of-concept or a larger one handling high volumes and heavy loads. Due to the need for flexible backend solutions, NoSQL databases have become increasingly popular. These databases provide support to applications that have a need for more flexibility in data structure compared to what a user can find in traditional structured databases.
What is a NoSQL Database?
A No-SQL database also referred to as a “not only SQL” or non-relational database provides a mechanism for retrieval and storage of data. It does not utilize table-based data storage, unlike traditional SQL databases. Based on their data model, NoSQL databases offer simplicity in design and can be of various types. Out of which documents, keys-values, wide columns, and graphs are the four main types. They provide flexible schemas, and they scale well with large amounts of data and heavy usage.
NoSQL databases store information in JSON files instead of columns and rows as in relational databases. But just to be made clearer, NoSQL is also referred to as ‘not only SQL’ which means you can combine the flexibility of JSON with SQL as well. Therefore, NoSQL databases are built to be flexible, scalable, and capable of quickly meeting the needs of modern businesses.
let us now move on to learn more about Amazon DynamoDB and MongoDB. The following information will help you to settle on the right database services suited for your application.
What is Amazon Dynamo DB?
Amazon DynamoDB, also known as Dynamo Database, is a hosted NoSQL database service provided by Amazon Web Services. For any application running on AWS, this cloud-based database platform provides scalability, high availability, and security. This database base service provider is fully managed and is known to provide value-added services and data documentation via Amazon Web Services. The AWS Management Console or DynamoDB API is used to interact with the service.
DynamoDB makes it easier to store and retrieve any volume of data needed to respond to any amount of traffic at any point. While maintaining low latency and predictable performance, DynamoDB eliminates traditional limitations on scalability. All the data is stored on solid-state drives, which ensure efficient handling of high-scale requests.
Since DynamoDB is a NoSQL database model, it allows documents, graphs, and columnar among many of its data models. DynamoDB tables allow users to store data and interact with it through GET and PUT queries, which are read and write operations, respectively. DynamoDB also supports conditional operations and basic CRUD functions. In DynamoDB, each item is uniquely identified by a primary key that the user specifies. For testing and development purposes, DynamoDB provides a limited storage, ever-free database instance to AWS users using their Free Tier.
DynamoDB is a particularly good fit for applications that require tight latency and demand a lot of data. As the data for your application grows, complex JOINs and SQL activities will slow down your queries. DynamoDB offers predictable latency for your queries even if the size is up to 100 TBs. DynamoDB has HTTP API and makes use of IAM rules for authentication as well as granting authorization which makes this database ideal for serverless applications.
DynamoDB enables you to offload the administrative burdens of operating and scaling a highly available database cluster, while still maintaining low latency and high performance. It does this by providing:
- A simple API for creating and administering databases
- Flexible data models for key-value or document data
- Automated storage scaling and partitioning
- Indexing for fast data access
- Integration with other AWS services for security and management
AWS DynamoDB Core Features
For high availability, scalability, and durability, DynamoDB carries out replication in over three availability zones. This NoSQL database also offers cross-region replication, which duplicates a table across one or more geographic regions.
Amazon DynamoDB secures its data in a table by using Fine-Grained Access Control (FGAC) for an administrator. FGAC manages credentials and permissions, its model is based on AWS Identity and Access Management services.
With AWS Lambda integration, DynamoDB enables a developer to create code-based actions on the basis of updates available in the table, such as connecting one data table to another source or sending over a notification.
If you’re considering using a NoSQL database for your next project, you may be wondering whether Amazon DynamoDB or MongoDB is the right choice. Both databases have their pros and cons, so it’s important to weigh your options carefully before making a decision.
To help you make an informed choice, let’s take a closer look at some more features of Amazon DynamoDB.
- DynamoDB is a fully managed service that runs on AWS, so you don’t have to worry about setting up or maintaining your own infrastructure.
- DynamoDB uses a novel partitioning scheme that automatically shards data across multiple servers, so it can handle very large-scale workloads.
- DynamoDB has built-in support for event-driven programming using AWS Lambda, so you can easily create real-time applications that respond to changes in your data.
- DynamoDB offers a generous free tier that includes up to 25 GB of storage and up to 200 million requests per month.
What is MongoDB?
MongoDB is one of the most robust document-oriented NoSQL databases available today. It is an open-source database with a non-structured query language. It is one of the most powerful NoSQL databases and systems available today.
MongoDB Atlas is a globally available cloud database solution for modern applications. MongoDB deployments on AWS, Google Cloud, and Azure can be seamlessly managed with this integrated automation and well-established processes.
This database solution gives adherence to high-level security to data and privacy standards. It is highly scalable and offers a unified platform comprising application services, search, mobile compatibility, and a global cloud database.
Because MongoDB is a NoSQL model, it allows space for various fields and structures for documents. Traditional rows and columns for data are not associated with relational database administration. The documents are stored in the BSON format, which is the binary version of JSON.
MongoDB’s data model is very extensive, it enables users to store data as well as integrate in various formats without compromising on the existing validation criterion, data access, or indexing. It doesn’t require downtime to make changes in the schemas. By doing so, you can spend less time preparing data for the database and instead spend more time optimizing your data.
MongoDB Key Features
It is Document Oriented
MongoDB, unlike RDBMS, stores all data in the form of documents rather than tables. In these documents, data is kept in key-value pairs rather than rows and columns, making the data far more flexible than in RDBMS, which assigns a unique ID to each document.
Schema-less database allows one collection to hold various types of documents. It is a great feature provided by MongoDB that enables the database to hold multiple documents which contain a different number of fields, sizes, and content.
Sharding is the technique to achieve horizontal scalability by taking data across numerous servers. Here the majority of data is divided into pieces by using the shard key. These data pieces are further evenly distributed across shards that stretch across multiple physical servers.
Another useful feature of MongoDB is indexing. This attribute allows indexing of every field in the documents with primary and secondary indices. Doing so makes searching for data from the repository much faster and easier. If the data isn’t properly indexed, the search of each document for every data query would take up a lot of time.
MongoDB can also operate on grouped data to provide a single or calculated output. The three types of aggregation available are aggregation pipelines, map-reduce functions, and single-purpose aggregation methods.
Here are some more features that make MongoDB stand out:
- Scalability: MongoDB is highly scalable, making it perfect for applications that need to be able to handle large amounts of data.
- Flexibility: MongoDB’s flexible schema allows you to store data in any format, making it easy to work with unstructured data.
- Performance: MongoDB is designed for high performance, with features like indexing and sharding that help you get the most out of your data.
MongoDB vs DynamoDB- Which One to go for?
MongoDB and DynamoDB are both amazing NoSQL databases that cater to user needs extensively. But it requires a fair bit of consideration when it comes to selecting what best suits the developers’ requirements. MongoDB and DynamoDB cannot be compared as both these database solutions are designed for distinct data requirements. For instance, Mongo DB is open source while DynamoDB is a fully managed NoSQL database solution whose services are provided via Amazon Web services.
When it comes to performance, DynamoDB is the clear winner. It’s designed to be scalable and can handle very large workloads. MongoDB is also scalable, but it doesn’t have the same level of performance as DynamoDB.
Ease of Use
DynamoDB is easier to use than MongoDB. It has a simple API and a straightforward data model. MongoDB is more complex, with a more flexible data model that can be difficult to work with.
Infrastructure & Data Management
All of AWS’s native NoSQL database solutions and features are readily available in DynamoDB. Yet, MongoDB offers enterprise-class NoSQL databases that are capable of multi-vendor, multi-cloud deployments without vendor locking users in.
Dynamo is recommended for low-latency workloads. It is a better option if you don’t have a dedicated operations person on your team. Yet its major drawback is locking-in vendors which don’t allow users to easily change the environment for deployment.
MongoDB is a NoSQL database program that comes from the availability of infrastructure and managed services from external sources. This means MongoDB solutions can be deployed in any environment of your choice. This is particularly important if you are concerned about vendor lock-in.
MongoDB has an advantage in its feature set for handling the fundamental data with native solutions for schema validations, indexing, and so on. Users can also customize it to meet most database requirements.
With DynamoDB you get the best of both worlds in terms of being user-friendly, integrations, and compatibility. Furthermore, users don’t have to stress about keeping the servers up and running for back-ups, monitoring, and provisioning.
While MongoDB Atlas solutions allow users to use any support from external cloud services providers to create data clusters and shift to the MongoDB database with little to no configurations. It offers a simple platform to manage its data clusters that spread across multiple cloud environments; however, it doesn’t have a tight integration product as you can find in DynamoDB.
DynamoDB has a lot more built-in features when it comes to data security. It comes with AWS identity and access management modules similar to other AWS services, as it is a part of AWS. What’s more, users enjoy an additional layer of security with DynamoDB as it is not easily accessible on the internet because of its unique setup.
On the other hand, MongoDB offers good security but it can only be leveraged after making changes to the setup in order to improve security. This implies MongoDB’s default implementation may not be that secure.
MongoDB has good security features as well, although they aren’t available by default. To put it another way, you’ll need to change the setup to improve security. As a result, MongoDB’s default implementation is not very secure.
DynamoDB is more expensive than MongoDB. DynamoDB charges per request, while MongoDB charges per GB of storage.
What Factors Should You Consider While Choosing Between DynamoDB and MongoDB?
There are a few key factors you should consider while choosing between Amazon DynamoDB and MongoDB for your project. These include:
- Data Model: DynamoDB uses a key-value store, while MongoDB uses a document-oriented model. This can impact performance and scalability.
- Query Language: DynamoDB has a proprietary query language, while MongoDB uses the popular JSON query language. This can impact developer productivity.
- Pricing: DynamoDB is more expensive than MongoDB on a per-gigabyte basis. However, DynamoDB offers a number of cost-saving features, such as reserved capacity and on-demand mode.
- Integration: DynamoDB integrates seamlessly with other AWS services, while MongoDB can be more difficult to integrate due to its lack of first-party support on AWS.
- Management: DynamoDB offers a managed service from Amazon, while MongoDB requires self-management or management from a third party. This can impact ease of use and total cost of ownership.
If you’re trying to decide between Amazon DynamoDB and MongoDB, it really depends on your specific needs. DynamoDB is a great choice if you need a fast, scalable database that can handle large amounts of data. MongoDB is a good choice if you need a flexible database that can be easily scaled. Ultimately, the best decision is to try out both databases and see which one works better for your particular project.
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