We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Comparing DynamoDB and MongoDB for Big Data Management
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Software > SQL > Comparing DynamoDB and MongoDB for Big Data Management
SoftwareSQL

Comparing DynamoDB and MongoDB for Big Data Management

DynamoDB and MongoDB are two great serverless database management tools that data-driven companies can use.

Albert Smith
Albert Smith
6 Min Read
background. Database and networking concept
DepositPhotos License: Author ayo888
SHARE

A growing number of companies are discovering the benefits of investing in big data technology. Companies around the world spent over $160 billion on big data technology last year and that figure is projected to grow 11% a year for the foreseeable future.

Contents
  • Where Can You Run Them?
  • What Are Their Ranges of Data Models?
  • How Much Do They Cost?
  • What Are Their Backup Capabilities?
  • How Secure Are They?
  • What is Indexing Like?
    • Decide Which Database is Right for You

Unfortunately, big data technology is not without its challenges. One of the problems companies face is trying to setup a database that will be able to handle the large quantity of data that they need to manage.

There are a number of solutions that can help companies manage their databases. They don’t even necessarily need to understand NoSQL to manage their databases. DynamoDB and MongoDB are both serverless services that are fully managed so you don’t have to deal with updates, maintenance, or paying for hardware, but they have significant differences. They also have similarities, which makes it a bit challenging to know which one is best for your needs.

Let’s compare the similarities and differences between these two solutions so you can make the right choice for your needs.

More Read

Handle Facebook Parse Migration the Expert Way
Handle Facebook Parse Migration the Expert Way
7 Big Data Trends That Will Impact Your Business
Splunk: Bringing Big Data Analysis to the Rest of Us
Using Microsoft Azure to Optimize Ecommerce Data for POS Solutions
AI Technology Leads to Innovative Photo Editing Software

Where Can You Run Them?

MongoDB and DynamoDB differ in the freedom they provide to run them. You can only deploy DynamoDB on Amazon Web Services (AWS), and it does not support on-premise deployments. With DynamoDB, you are essentially locked into AWS as your cloud provider. MongoDB is deployable anywhere, and the MongoDB Atlas database-as-a-service can be deployed on AWS, Azure, and Google Cloud Platform (GCP). It is compatible with a laptop to mainframe and on-premise through a hybrid cloud. You can also easily monitor these databases.

What Are Their Ranges of Data Models?

MongoDB has a wider range of datatypes than DynamoDB, even though both databases can store binary data. DynamoDB is limited to 400KB for documents and MongoDB can support up to 16MB file sizes. DynamoDB also lacks a date type and is primarily a key-value store. With MongoDB, you get a wider variety of use cases such as geospatial queries, graph traversals, and more.

How Much Do They Cost?

There is no straight answer for this for either solution because you need to use their pricing calculators to input the various factors that influence the cost. Both have free tiers so you can see if they work for your particular use cases, but for most large-scale applications, MongoDB typically ends up being cheaper. Your MongoDB service cost is calculated based on your storage and cloud provider. Your DynamoDB cost factors in if you need it provisioned or on-demand, how much data storage you need, the number of reads and writes required, and backup needs.

What Are Their Backup Capabilities?

The two systems are relatively similar when it comes to backup. MongoDB offers on-demand, continuous backups — as does DynamoDB. But MongoDB also offers filesystem snapshot backups and queryable backups. You don’t get queryable backup on DynamoDB and you might need to manually recreate many configurations that are not backed up.

How Secure Are They?

DynamoDB is generally considered to be the more secure of the two — with the full power of AWS’ security measures behind it. DynamoDB integrates with AWS security services so you can use your own encryption keys, which you can do as well on MongoDB using the key management system available on whatever cloud provider you utilize. But MongoDB installs with authentication off as its default, which has led to data loss for some users. You have to activate security by enabling user authentication with usernames and passwords, while all data in DynamoDB is encrypted at rest and in transit.

What is Indexing Like?

On MongoDB, there is no extra cost to index your data, and it’s easy to develop against the system. Indexes are consistent with underlying data, and you can define secondary indexes on any field at any time. DynamoDB is a bit more limited and complicated to manage as indexes are sized, billed, and provisioned separately from your data. Applications might end up handling stale data as global secondary indexes (GSIs) be inconsistent with underlying data. For these reasons, your data integrity in MongoDB is more strongly consistent than in DynamoDB.

Decide Which Database is Right for You

If you have questions about how to eliminate data pain points in your organization and how to unlock all the information you need from your databases, apps, and files, consider a comprehensive enterprise solution for your complex data needs.

TAGGED:databaseDynamoDBMongoDB
Share This Article
Facebook Pinterest LinkedIn
Share
ByAlbert Smith
Follow:
Albert Smith is a Digital Marketing Manager with Hidden Brains, a leading IT company specializing in enterprise and emerging technology solutions such as Blockchain development , IoT, Cloud, Chatbot and Big Data. He provides innovative ways to help tech companies, startups and large enterprises build their brand.

Follow us on Facebook

Latest News

Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security
Flat editorial illustration: The article's core relationship is the alignment between customer behavioral data (visit frequency,
Data-Driven Loyalty: How Restaurants Use Behavioral Analytics to Optimize Revenue
Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

How NASA Tackles Big Data with MySQL
New ProductsSQL

How NASA Tackles Big Data with MySQL

7 Min Read
Starting Your Business: Data From the Ground Up
Business IntelligenceData Mining

Starting Your Business: Data From the Ground Up

4 Min Read
What Data-Driven Companies Must Know About NoSQL Database
SQL

What Data-Driven Companies Must Know About NoSQL Database

8 Min Read
Analytics: Not About Saving Time
Analytics

Analytics: Not About Saving Time

7 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
ai chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?