DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Please enter at least three characters to search
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

Zones

Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Last call! Secure your stack and shape the future! Help dev teams across the globe navigate their software supply chain security challenges.

Modernize your data layer. Learn how to design cloud-native database architectures to meet the evolving demands of AI and GenAI workloads.

Releasing software shouldn't be stressful or risky. Learn how to leverage progressive delivery techniques to ensure safer deployments.

Avoid machine learning mistakes and boost model performance! Discover key ML patterns, anti-patterns, data strategies, and more.

Related

  • Java and MongoDB Integration: A CRUD Tutorial [Video Tutorial]
  • MongoDB to Couchbase for Developers, Part 1: Architecture
  • Oracle BI vs. Tableau: Which Business Intelligence Tool Is Better?
  • MongoDB to Couchbase: An Introduction to Developers and Experts

Trending

  • Unlocking the Potential of Apache Iceberg: A Comprehensive Analysis
  • 5 Subtle Indicators Your Development Environment Is Under Siege
  • A Developer's Guide to Mastering Agentic AI: From Theory to Practice
  • Measuring the Impact of AI on Software Engineering Productivity
  1. DZone
  2. Data Engineering
  3. Databases
  4. How to Visualize and Understand Your MongoDB Data

How to Visualize and Understand Your MongoDB Data

Check out what MongoDB is as well as some data visualization tools. Also look at MongoDb for real-time analytics.

By 
Veronika Rovnik user avatar
Veronika Rovnik
·
Updated Aug. 29, 18 · Opinion
Likes (12)
Comment
Save
Tweet
Share
18.1K Views

Join the DZone community and get the full member experience.

Join For Free

One of the essential pillars of modern real-time applications is their elasticity. Therefore, choosing the database for an application can be a real challenge. Different database designs serve different purposes, and for this case, relational databases don’t fully meet the needs of developers because of their rigid schemas and constraints on data types.

Elasticity can be provided by using a flexible database, which is able to handle big amounts of mostly unstructured data and increase/reduce storage capacity without loss when the business requirements are suddenly changed.

Therefore, NoSQL databases gradually displace the relational ones: their capabilities can meet the challenges of modern, usually unstructured, data.

MongoDB is ahead of all other NoSQL databases and fulfills business requirements on fast and flexible access to the data in various spheres of development, especially where a live data prevails. The great news is that ACID transactions are supported starting from MongoDB 4.0.

To be sure, you can check a credible spline chart of DB-engines ranking on databases trends over years and compare usage of MongoDB to the usage of other databases.

Let’s dive deeper into the technical aspects of MongoDB and its advantages.

What is MongoDB?

MongoDB is a document-oriented database. It means that all the data is stored in JSON-like documents which are stored in collections in its turn — an analog of the tables in relational databases but without specified relations between them. It is optimized for natively storing the documents and other types of data.

Why Use MongoDB?

I’d like to point out the most compelling features of MongoDB:

  • Dynamic schema: you don’t need to predefine the schema in advance at the moment of collection creation; you can change fields’ types, their number and size of the document at any time. Creation of dynamic data models is thus provided. That is what is called a flexibility of MongoDB. It finds its recognition in an agile development.
  • Support of indexing, dynamic queries on documents, and real-time aggregation for powerful data analysis.
  • Scalability. That means that you can spread the data across multiple servers easily without threats to its availability. The same cannot be said about the approach used in relational databases.
  • No need in mapping the application’s business objects to database tables (for example, as in Java using JPA). Therefore, it’s easy to work with data.
  • Support of auto-sharding, which enables horizontal scaling. Horizontal scaling requires adding servers which usually costs lower than using a more powerful CPU (a vertical scaling). MongoDB shards data at the collection level.
  • Cross-platform compatibility.
  • The last but not the least: it’s free and open-source.

However, I should mention that there always existed a trade-off between flexibility and reliability. The latest usually involves ACID compliance and is provided by SQL databases. So it’s up to you what database to choose for your application — a relational or NoSQL one.

MongoDB for Real-Time Analytics

If your data is growing and changing its structure once in a while, the natural question arises: how to handle and process all of that data? Here comes in handy the functionality of NoSQL databases and MongoDB in particular. MongoDB is optimized for natively storing documents and their fast accessing by indexing, also, the replication is supported. Therefore it is much faster than its relational competitors. To enhance existing optimization, you can search for different techniques which include using WiredTiger engine, zone-based sharding, choosing short names for fields, etc.

The fact that MongoDB is in favor of such companies as Google, Cisco, SAP, Facebook, Expedia, and others speaks for itself. It is commonly used for real-time analytics, big data, mobile applications, etc. MongoDB is the best decision for unstructured and semi-unstructured data such as:

  • Posts in social media
  • Web pages
  • Emails
  • Reports
  • Medical records
  • Raw data from marketing researches
  • Scientific data
  • And other

Besides, it greatly copes with storing structured data as well.

Available MongoDB Data Visualization Tools

Whatever type of data you choose, sometimes it becomes necessary to visualize all the data or its part. When searching for MongoDB data visualization tool, I’ve noticed that it is hard to find the one with out-of-the-box functionality. So today I’ll give you a rundown of the tools which I’ve used together to visualize my data.

  • The first one is Compass, which is a native MongoDB database management GUI application. It is a part of MongoDB Atlas subscription. Nevertheless, Compass offers a free trial during which I’ve managed to fully test the application. I've discovered that it is suitable for visualization of MongoDB data and its collection’s schema; editing, adding and deleting data; I’ve used it instead of the mongo Shell and got even better results while working with the data. Also, I’ve used a Schema visualization tool to get the new insights and define the patterns in my dataset. This is what its interface looks like: Image titleI think it is one of the most powerful parts of Compass because it makes me able to interact with my data in real time, quickly perform simple and complex queries to filter the data and see the specific portions of it, analyze the distribution of data types and fields’ values using generated histograms.
  • The second data visualization tool my choice fell on is Flexmonster Pivot Table. It is a component for web reporting and data analysis. It supports connecting to JSON data sources so I created a Node.js application and set up a connection to MongoDB, then loaded my data into the pivot table. Then I analyzed the data applying sorting, filtering, and aggregation via a comfy UI.
  • Flexmonster offers a free trial that allowed me to evaluate all the features and functionalities.

    Also, I’ve noticed that while Compass is installed as a stand-alone application, Flexmonster needs to be embedded into the web application. I have an Angular 4 application and sometimes it takes a while to integrate a new tool into it. But in the documentation, I’ve found a tutorial that helped me to accomplish this task quickly.

    Image title

    To start getting insights into data, you can request the data from the MongoDB database and load it right into the pivot table. I’ve used this tutorial to get the data into my Node.js application.

    I hope you will try both tools to achieve your most sophisticated MongoDB data analysis goals. Feel free to experiment with Compass and Flexmonster Pivot Table and see how their functionalities complement each other.

    I would love to hear your feedback on this review. Please let me know what you think in the comments. What tools do you use for MongoDB data visualization? Do they meet all of your requirements?

    Data visualization MongoDB Database Relational database

    Opinions expressed by DZone contributors are their own.

    Related

    • Java and MongoDB Integration: A CRUD Tutorial [Video Tutorial]
    • MongoDB to Couchbase for Developers, Part 1: Architecture
    • Oracle BI vs. Tableau: Which Business Intelligence Tool Is Better?
    • MongoDB to Couchbase: An Introduction to Developers and Experts

    Partner Resources

    ×

    Comments
    Oops! Something Went Wrong

    The likes didn't load as expected. Please refresh the page and try again.

    ABOUT US

    • About DZone
    • Support and feedback
    • Community research
    • Sitemap

    ADVERTISE

    • Advertise with DZone

    CONTRIBUTE ON DZONE

    • Article Submission Guidelines
    • Become a Contributor
    • Core Program
    • Visit the Writers' Zone

    LEGAL

    • Terms of Service
    • Privacy Policy

    CONTACT US

    • 3343 Perimeter Hill Drive
    • Suite 100
    • Nashville, TN 37211
    • support@dzone.com

    Let's be friends:

    Likes
    There are no likes...yet! 👀
    Be the first to like this post!
    It looks like you're not logged in.
    Sign in to see who liked this post!