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MongoDB

MongoDB

Overview

What is MongoDB?

MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with…

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Recent Reviews

TrustRadius Insights

MongoDB has emerged as a popular choice for developers and organizations seeking a fast and efficient NoSQL data layer for their web …
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Oleg's MongoDB review

10 out of 10
January 17, 2022
We use it as one of the internal database types in our REST APIs via a Spring/JAP connection in high-load applications. MongoDB is highly …
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Stable & Easy to Use

8 out of 10
May 21, 2021
Incentivized
MongoDB was our first NoSQL database usage. For this reason, we assigned it to an application that serves inside our IT infrastructure. As …
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No relation, no worry

10 out of 10
May 08, 2021
Incentivized
Used as a database solution for a web application for storing all data needed. That means all user details, application configuration and …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 7 features
  • Availability (38)
    9.7
    97%
  • Performance (38)
    9.0
    90%
  • Concurrency (38)
    8.6
    86%
  • Security (38)
    8.6
    86%
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Pricing

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Shared

$0

Cloud
per month

Serverless

$0.10million reads

Cloud
million reads

Dedicated

$57

Cloud
per month

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://www.mongodb.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Starting price (does not include set up fee)

  • $0.10 million reads
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Product Demos

MongoDB Change Streams: The Hidden Gem within the MongoDB Repertoire

YouTube

MongoDB & Tableau FAA Demo

YouTube

NoSQLMap MongoDB Management Attack Demo

YouTube

Intro to MongoDB with C# - Learn what NoSQL is, why it is different than SQL and how to use it in C#

YouTube

MongoDB with Python Crash Course - Tutorial for Beginners

YouTube
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Features

NoSQL Databases

NoSQL databases are designed to be used across large distrusted systems. They are notably much more scalable and much faster and handling very large data loads than traditional relational databases.

9.1
Avg 8.8
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Product Details

What is MongoDB?

MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

MongoDB's flagship Enterprise Advanced edition is a collection of products and services that drive security, efficiency, to put users in control of MongoDB Databases. These include:

  • MongoDB Enterprise Server - the commercial edition of MongoDB, which includes additional capabilities such as in-memory storage engine for high throughput and low latency, advanced security features like LDAP and Kerberos access controls, and encryption for data at rest. Enterprise Server is included with the MongoDB Enterprise Advanced subscription, which includes expert assistance and tools. Or, the MongoDB Enterprise Server is also available free of charge for evaluation and development purposes.
  • MongoDB Ops Manager - Tools for managing MongoDB in a secure, on-premise or owned environment. Available through the MongoDB Enterprise Advanced subscription, Ops Manager eliminates operational overhead by automating key administration tasks such as deployment, and upgrades. Tools also support monitoring with visualization of performance metrics, continuous or point-in-time incremental backup, and query optimization with the Visual Query Profiler.
  • MongoDB Enterprise Kubernetes Operator - Kubernetes Operators are application-specific controllers that extend the Kubernetes API to create, configure, and manage instances of stateful applications such as databases. On self-managed infrastructure – whether on-premises or in the cloud – Kubernetes users can use the MongoDB Enterprise Operator for Kubernetes and MongoDB Ops Manager or Cloud Manager to automate and manage MongoDB clusters.

MongoDB is available as a managed cloud solution via MongoDB Atlas. But MongoDB Enterprise Advanced offers advanced access control and data security features to protect on-premise or private cloud databases, and satisfy compliance or customer requirements. It’s also designed to make it easy to integrate MongoDB with any existing security infrastructure and tooling.


Organizations from startups to the largest companies can use MongoDB's capabilities to create applications never before possible at a fraction of the cost of some legacy databases. The MongoDB database ecosystem boasts over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.

Also, the MongoDB Community Edition is licensed under what the company provides as the Server Side Public License (SSPL), which is based on the GPL v3. All MongoDB Community Server patch releases and versions released on or after October 16, 2018, will be subject to this new license, including future patch releases of older versions. The Community version of the distributed database offers a document data model along with support for ad-hoc queries, secondary indexing , and real-time aggregations to provide ways to access and analyze data.

MongoDB Features

  • Supported: Comprehensive monitoring for full-performance visibility
  • Supported: Automated database management for 10-20x more efficient ops
  • Supported: Fully-managed backup for peace of mind

MongoDB Screenshots

Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of

MongoDB Video

What's New in MongoDB 7.0 Explained in 3 minutes

MongoDB Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

MongoDB starts at $0.1.

Couchbase Server, Azure Cosmos DB, and Amazon DynamoDB are common alternatives for MongoDB.

Reviewers rate Availability highest, with a score of 9.7.

The most common users of MongoDB are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(435)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

MongoDB has emerged as a popular choice for developers and organizations seeking a fast and efficient NoSQL data layer for their web applications. Its flexibility and iterative development capabilities have made it invaluable in various use cases. For example, MongoDB is being utilized by engineering departments to power SaaS platforms, allowing clients to create and configure assets for account-based marketing efforts. The document store of MongoDB proves ideal for handling complex configurations with nested structures. Additionally, the native JSON support is convenient and valuable when working with data needed in web browsers. MongoDB's aggregation framework enables the generation of complex reports and dashboard reports, which are immensely beneficial for businesses. The replication feature of MongoDB seamlessly allows applications to scale and support numerous clients, further enhancing its utility.

Furthermore, MongoDB has proven its worth as a temporary mid-size storage database for processing massive amounts of data per day and extracting notable events and records for further analysis. It facilitates quick application development in the cloud, enabling free usage and evaluation of system loads. Additionally, MongoDB serves as an internal database type in REST APIs for high-load applications. Compared to traditional SQL systems, MongoDB stands out due to its scalability and superior performance in terms of reads and writes. Its simplicity and clarity make it a preferred choice when dealing with large amounts of data. Furthermore, MongoDB is extensively used as the main storage technology for web development projects employing the MEAN Stack. Its scalability and unstructured document storage are particularly valued from a business perspective.

Moreover, MongoDB's non-relational nature simplifies database modeling and optimizes performance when working with JavaScript or JSON objects. It has been recognized for optimizing delivery time, making projects more feasible within specified timelines. MongoDB is widely employed as the main persistent datastore for SaaS offerings, providing robust and scalable solutions. It finds immense utility in large-scale, high-transaction environments as well by storing analytics information from social networking sites or serving as the primary datastore for Intranets. Additionally, MongoDB handles data with hundreds of variances effectively, which can be challenging to manage in a relational database. Its lightweight alternative for front-end-heavy projects and document-based data storage makes it a compelling choice over traditional RDBMS solutions. Consequently, MongoDB proves useful for managing a large amount of information, making it a preferred choice for banks and large institutions.

Moreover, MongoDB's application extends to various domains such as train yard management applications, where it enables easy management of JSON structures within a database. Gradually, MongoDB is being adopted by different teams and products after resolving scaling and sharding issues. It is highly regarded by software development teams for its efficiency, easy learning curve, and efficient query languages. MongoDB bridges the gap between data analysis and developers by facilitating the structuring of databases and primary querying. Consequently, organizations across industries utilize MongoDB for developing internal applications as well as apps for other companies.

MongoDB's robustness and scalability make it suitable for handling millions of unstructured records, such as defect management in software projects. It excels at building multiple dashboards and metrics from data using simple find queries, aggregation, and MapReduce operations. MongoDB also serves as a reliable storage solution for handling intense database use cases, storing critical customer information, rules, configuration data, and content for alert notifications and statements.

The horizontal scale-out capabilities of MongoDB coupled with its ability to work with complex structures of information make it a chosen technology for many applications. Its ease of use during the initial stages of a project and its ability to handle data increase quickly are additional reasons why programmers favor MongoDB. It is commonly used as a store of user accounts and app settings for mobile apps implemented in JavaScript and Node.js.

Furthermore, MongoDB helps improve response times by scaling systems horizontally and distributing the load effectively. It supports agile methodology software development life cycles with its dynamic schemas, which facilitate iterative development and rapid prototyping. Developers appreciate MongoDB as an efficient NoSQL database that offers scalability coupled with good support and helpful documentation.

Additionally, MongoDB solves performance problems in APIs by providing an easy-to-scale solution while enabling developers to work in an agile manner and improve response time. Its ability to store non-relational data like user profiles and application logs makes it a popular choice among developers who need to work with diverse datasets. Moreover, MongoDB enables fast prototyping of new APIs by saving time wasted on data conversion.

MongoDB's versatility extends to various programming languages and operating systems without posing any challenges. It has gained significant traction in the academic community, with students utilizing MongoDB extensively in software engineering projects. It serves as a valuable tool in testing environments, helping students understand popular NoSQL databases and preparing them for development positions.

Furthermore, MongoDB is the preferred choice for managing transactional databases in gaming, offering features like replica sets, sharding, and clusters. Its flexibility and quick prototyping capabilities make it the main database for SaaS products, allowing for the easy exploration of new product ideas.

In a web application context, MongoDB acts as a comprehensive storage solution, hosting all necessary data including user details, application configuration, and user-managed data. It serves as an internal database type for organizations, handling millions of records across multiple departments.

MongoDB's capabilities extend beyond traditional web applications. It plays a crucial role in messaging systems, allowing for fast subscriber finding and efficient message sending. Its ability to model non-relational data when defined schemas do not suit the dataset makes it extensively used in various business-facing applications built with different front-end technologies.

Additionally, MongoDB powers web platforms, internal tools, and other applications as a primarily NoSQL database solution. It is leveraged by multiple departments within companies to store and process large volumes of records. MongoDB's versatility also shines in managing complex portals that showcase student assessments and support B2B reporting.

Moreover, MongoDB serves as a reliable datastore for extensive big data associated with users in an application. Compared to SQL Server, MongoDB provides a better platform for big data storage and analysis. Its capabilities are harnessed by storing and retrieving data for complex portals, enabling effective B2B reporting.

In conclusion, MongoDB has proven its worth across a wide range of use cases. From empowering SaaS platforms and handling complex configurations to supporting dashboard reports and scaling applications to serve numerous clients, MongoDB offers flexibility and efficiency in managing data. Its performance advantages over traditional SQL systems, scalability features, compatibility with JavaScript and JSON objects, ease of use for developers, and extensive documentation contribute to its widespread adoption across industries. Whether it's powering web development projects or managing transactional databases for gaming, MongoDB continues to be an instrumental tool in modern software development and data management.

Based on user reviews, the most common recommendations for MongoDB are as follows: Consider MongoDB for specific use cases such as applications where delays are acceptable or rapid prototyping and automatic shredding of data. It is also suggested for full-stack web development with JavaScript and implementing JSON-style database storage.

Evaluate data needs and scalability by analyzing data requirements before deciding to use MongoDB, especially if the data is relational. Consider MongoDB's ability to store large amounts of data and apply sharding mechanisms for scalability.

Seek professional help and resources during the early stages of MongoDB adoption. Stay in touch with MongoDB professionals in enterprise environments. Utilize resources like MongoDB University for learning purposes, proper documentation, and online guides for installation. Additionally, test MongoDB before implementation and benchmark against other databases for comparison.

It's important to note that these recommendations are based on user opinions and their applicability should be evaluated based on individual requirements and circumstances.

Attribute Ratings

Reviews

(26-50 of 66)
Companies can't remove reviews or game the system. Here's why
Score 9 out of 10
Vetted Review
Verified User
Incentivized
In the beginning, we considered several products in the market. Since our project was a science and research project, our budget wasn't as big as a commercial project, but still, we wanted the product to be scalable so that we could deal with "smooth transition" from research to commercialization. At the end of the discussion, we choose MongoDB rather than other products like Cassandra, simply because we could hire good developers who had expertise in MongoDB. Our management left that decision to developers and let them choose since they knew what's good for them.
Gabriel Samaroo | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is the best NoSQL database out there. There are others, but Mongo has the largest community, is very easy to set up, and is extremely performant. Compared to a relational DB (like MySQL or Postgres) is like comparing apples and oranges. One isn't better or worse than the other. It more depends on the particular data you are working with and what you need to do with that data. That will determine which option to go with.
Bill Hefty | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
MongoDB seemed to be a bit more robust in schema models at the time of choosing it over Firebase. Firebase was also still in beta at the time. Since then I have used both MongoDB and Firebase Real-time Database, and feel that firebase is easier to get running and started, but I still prefer some of the data structures and querying of MongoDB.
Ronald Melendez | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is probably the most famous NoSQL database of the moment. it has become one of the most promising startups. Some companies that currently use MongoDB are Foursquare or eBay. This type of database is designed to perform queries and aggregations on large amounts of data. They work in a similar way to relational databases, but storing columns of data instead of records.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
I love MySQL, but again, it's a totally different use-case. For something with so much varied data in no particular form or structure that needs to be pooled together in a "data lake," a NoSQL solution like MongoDB is an easy choice. It makes it so much easier not having to deal with constraints you would be responsible for defining otherwise.
Brett Knighton | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Looking into PostgreSQL happened post move to Mongo. Had we considered both options at the time we likely would have went with PostgreSQL. We may migrate at some point in the future but currently it doesn't make sense.
Joshua Weaver | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
  • Firestore
I recently tried out Firestore from the Google firebase family of development products. While it allows structuring of data similar to MongoDB, it handles things a little differently. MongoDB documents are incredibly flexible and can be structured really any way you can structure a JSON object with a few additions. I felt like Firestore's query syntax was super easy to grasp, although it wasn't as powerful or flexible straight away as a MongoDB query. For example, you can combine a lot more logical operators easily in a Mongo query while I couldn't figure out how to do so on a Firestore query. And there's no regex search for text-based/full-text searching in Firestore like there is in MongoDB. I ended up ditching Firebase after a while because it had other limitations that weren't right for our project. However, I would still choose it for certain projects if I found it to be a good fit for the project and benefited from having an integrated data layer. It made a lot of other app development hurdles like authentication painless and easy.
Jon Kern | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
I only briefly looked at CouchDB after I already began using MongoDB. Naturally, I have used many relational SQL databases.

Since MongoDB did everything I needed, I saw no need to look around for alternatives.

(Okay, full disclosure. I am an "association" vs "inheritance" object-oriented snob. In Rails, ActiveRecord implements persistence via inheritance for SQL databases. The MongoDB gems like mongoid and mongomapper add persistance via association. Boom!)
September 21, 2017

Awesome Product

Apnesh Sharma | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We wanted to go a schema-less database like MongoDB. We needed faster turnaround in development, and MongoDB has the best features of key/ values stores, document databases and relational databases in one. Because it uses tables, stored procedures are no longer required. MongoDB is relatively new player in the data storage world when compare to giants like Oracle, but it has drawn a lot attention because of its distributed key value store.
September 12, 2017

MongoDB - A perspective

Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • SQL
There are use cases for both relational and non-relational databases. MongoDB is simply a different method of storing data, but I find it to be faster and more intuitive than relational models.
Adrián Rivelli | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
In comparison with other no-sql, mongodb have some important benefits, the community, the official support, and the most important thing Its to want to solve all the problematic of the storage, this new versions include graphs, text search and other tools, expanding their abilities and capabilities.
Jeff Sherard | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.

Other platforms had specific parts of what we were looking for - MongoDB had it all.
Niraj Adhikary | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
From the beginning, we thought we would have a large volume of data, so MongoDB was a natural choice. Next we started the project and found MongoDB is also developing new features that are more like SQL which was very nice for us. As data volume is growing with time, no need to think of anything else.
Arnold Daniels | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is very specific, making it not a good candidate for the bread-and-butter DB.
Score 9 out of 10
Vetted Review
Verified User
Cassandra: may be better for bigger use cases, in PB range, due to our use cases being slightly smaller, we did not need this, but we highly rely on efficient indexing, and low latency, which seemed to be better based on our testing in Mongodb.
Couchbase Server: Document features are not mature yet enough, and they are not/may not the main focus of the solution, so in some of our use cases, where advanced querying and indexes were necessary, we found MongoDB a better fit.
Hadoop: very powerful for batch operations, but not really good for OLTP like functions, the realtime capabilities are not the main focus, so Mongodb performs better and more economical in such use-cases.
Score 5 out of 10
Vetted Review
Verified User
Incentivized
Relational DB are not efficient when storing data structure like JSON. Different data structure can be stored without defining the schema. Most relational db might store data like Json as blobs. One single entry would store the entire JSON as blob and you can't query the structure to find out the various data in JSON. You would have to retrieve the whole structure and parse it. Or parse the whole JSON and store the appropriate value of key to a corresponding column in the DB. In MongoDB you can query the single document and also fetch the data of all key value pairs and also its nested key value pairs directly.
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