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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

(431)

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

(1-23 of 23)
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Kendal Droddy | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
In my organization, we use MongoDB as a temporary mid-size storage database. We have very large databases and process a massive amount of data per day. Throughout the day we identify notable events and records and need to extract them for continued analysis. This is where our MongoDB environment comes into play. We roll all of these detected records into MongoDB for further use.
  • Very simple with easy to learn and understand syntax.
  • Offers great flexibility as their is no predetermined schema.
  • Scalable - handles all our our data very effectively even as we scale up.
  • Data duplication can be a problem - have to make a concerted effort to avoid this.
  • Memory usage can be an issue depending on infrastructure.
  • Certain commands that may work well in something like MySQL may not in MongoDB, such as join commands.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Pablo Alejandro Laborde | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We install it for a video-on-demand system (like Netflix) for Argentine productions (series, short films, and films). I participate in architecture design, MongoDB database environment creation, and their administration.
  • Scalability
  • High Availability
  • Easy to install
  • Free training
  • Offices in south america to provide more sales markets
The best for document databases
Balázs Kiss | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
MongoDB serves as a local dev database and as a production database for some of our microservice solutions. We use it for front-end-heavy projects and storing document based data, where original RDBMS solution would be overkill.
  • Document-based information storing and retrieving.
  • Indexing and querying small documents from a big heap of files.
  • Integrating with JS-based backend.
  • By design, joined collections tend to be much slower than in relational DB.
  • Some kind of relational model support.
MongoDB is an excellent tool to start development fast on a smaller POC, or, to serve as a backend for storing raw json-based data as well. It can be used for emulating a relational database but its core strength is storing the redundant, non-BCNF data, and querying it. So if we have any of those, MongoDB can serve as the DB with a really fast initialization in the development process - but just as well as in production.
Jose Manuel Ortega | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB as the main storage technology at the backend level for projects related to web development using the MEAN Stack (MongoDB, ExpressJS, AngularJS, NodeJS).

From a business point of view, the best features it provides are scalability and unstructured document storage, which allows us to have a flexible schema for the data.
  • Load balancing and data replication
  • Indexing and Document validation
  • Support for different programming languages and integration with different frameworks
  • Good query performance
  • Not the best solution for applications with complex transactions and many parallel operations
  • It is not an optimal solution if the application needs to update the database frequently.
  • Usually requires more disk space
As a developer, the main reason for using MongoDB is its speed and its ability to add records with different fields to the same collection in a much more flexible way than a database based on a relational model. For example, a document can be used to represent a blog and the associated comments can be placed as an array in the main document. This makes data easier to manage, eliminating the "JOIN" operation that affects performance and horizontal scalability in traditional relational databases.

As for less favorable scenarios, they could be those applications that need to perform frequent updates with many transactions, for example bank transactions.
February 26, 2020

Fast, easy to use!

Duncan Hernandez | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is currently being used to structure our databases and our primary querying tool. What is convenient about it is that you can change tables without writing lots of code. All data is stored in javascript, which is what all of our programmers use, so the gap between data analysis and our developers is lessened.
  • Schema-less database, which means easy to scale.
  • Easy indexing gives better query times.
  • Not a relational database. Lots of capabilities lost here.
  • No joins, which is new to me.
The tool is very easy to set up and start developing right away. I found it extremely simple to start utilizing in a short period of time. Mongo is more suited for people not concerned with back end logic as there is no joining like in a typical relational database scenario. However that could cause disruption to the people used to seeing relational databases.
Chi Anh La | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
I am using MongoDB as our database back-end system. It's an efficient NoSQL for scalability. The support is good and new features were added in every release. Documentation is helpful and complete for many use cases.
  • Horizontal scaling with shard cluster
  • Helpful documentation
  • New and meaningful features in yearly releases
  • Aggregation framework for reporting application
  • Transaction not supported on sharded collection
  • Documentation is complete but not well structured
  • Support for MongoDB customers should be improved
MongoDB supports JSON Schema data with the most complete NoSQL query framework among all NoSQL databases. The shard cluster is well designed for large applications with multiple concurrent users. It is best suited for applications that store data mostly for reading and reporting. But it will be improved towards applications with more write operations as well in future when transaction are supported on shard cluster (expected in version 4.2).
February 23, 2019

MongoDB Review

Score 8 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is a NoSQL backend storage database that we use extensively for modeling non-relational data. NoSQL databases tend to shine when defined schemas do not well suit a data set — perhaps the dataset is highly variable in the data that it holds from one entity to another, or perhaps the data's structure is simply not well understood. NoSQL and MongoDB are great for this situation.
  • Simplifies modeling complex, non-relational datasets.
  • Strong open source community.
  • Has solid libraries in a variety of implementation frameworks — e.g. Node JS and Mongoose.
  • Documentation is at times overly difficult to understand.
  • Versioning became confusing between major versions 3 and 4, with many still working on and implementing 4.
  • Lacks some of the nice-to-have features of more mature, generally relational databases like MySQL or PostgreSQL.
Amongst situations where the data being modeled is not well structured, using a NoSQL database — and using MongoDB in particular — may be a great choice. While Mongo *does* let you get away with less structure, you must be aware that less structure is not always the correct development avenue to take. Not having to manage a database schema does not necessarily make your development speed any faster.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
The software has the facility to balance loads which allow [for] better storage of files and no need to pay for the license. It is a completely free of cost software; it contains high security.
  • No need to write a complicated query such as MySQL. Writing the query in MongoDB is easier as compared to MySQL.
  • 3rd-party libraries and framework support are increasing day by day.
  • We get too many tutorials for understanding MongoDB. Provide a proper tutorial which is easier for a developer to understand the code.
  • Adding more and more features will motivate the developer to use MongoDB.
  • Third party library should be increased.
We can store a large volume of data that have no structures. We can develop and release quickly.
Ronald Melendez | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We have been able to take advantage of this tool since being a non-relational database, it is much easier to build the model of the architecture of the database model. This makes the development time much easier. When working with javascript language, or working with JSON objects and collections, MongoDB makes the connection of services for queries much lighter and optimizes the performance of the applications. Also, you can work, in case you do not know the console commands, with a Desktop database administrator in a graphical way. The learning times really are much faster, which allows a great scalability of the project. In the development department, this optimizes the delivery time with the clients, which makes the projects much more feasible in terms of delivery times.
  • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
  • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
  • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
  • MongoDB seems to be one of the most complete tools in its field, I believe that it has all the features that a non-relational database should have.
  • Perhaps because it is a relatively new tool there are very few experts in the field of MongoDB.
Mongo DB is better placed in large projects, with great scalability. It also allows you to work quite comfortably with projects based on programming languages such as javascript angular typescript C #. I believe that its performance is much better with the type of technologies that handle very logical, similar terms of programming. If we use languages like java php, for example, it is better to work with relational databases like postgres or mySql. Since this type of technology allows you to work better with database management frameworks much more agile for these environments, such as JPA, HIBERNATE, Oracle, I think they are much better with this type of architecture and programming languages.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is used as part of a security intrusion detection system, which keeps track of security events. These events, or indices, contain data pretaining to security related data, such as authentication, sign in history, etc. There can be a lot of these events and MongoDB is used as a no fuss store that can easily accept all kinds of data from requests we get.
  • We get a lot of data in, with various schemas depending on the request so MongoDB is a great pool for all the data.
  • It's simple, and the fact that it's non-relational makes it easy to add data from the pipeline.
  • Since it's all JSON it's super easy to pass it all into the frontend with a request.
  • Two edged sword, since it's not a relational db the data is kind of "loosey-goosey" and can be hard to keep track of.
  • It's newer than something like MySQL, and also has a different use case, but as such has less community support.
  • Compared to MySQL it's a heavier product.
It depends on what your project is. If you're doing some crazy data analytics where it might be useful to have a giant pool of relatively unstructured data that needs to be piplined into some kind of visualization, then MongoDB might be a good idea. If you want to create a database with structure and a well-defined schema, well, then you need to look elsewhere.
Miguelangel Nuñez | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB in the company's software development department to storage a large set of data for a meteorological forecast application. The data were provided by a third party service and refreshed every 5 minutes. Mongo was chosen to manage all the data. It's also used for a service of dynamic forms developed in the company.
  • With the ideal performance configuration, MongoDB is a great tool to manage data in a blazing fast way.
  • The document-oriented database has certain advantages: good fit for modern JavaScript frameworks (direct use of JSON), flexibility, big data processing and real time statistics/data analysis.
  • MongoDB is very easy to understand.
  • The resulting database is heavier than in a SQL relational database system
MongoDB is an excellent option for small / medium projects where relationships are not very important. When you have a lot of table relations, it is better to use a relational database.
Sonaj Gupta | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Yeah, I liked this MongoDB advanced version of SQL we solved many businesses problems with MongoDB. It stores huge amounts of data used by our organization to store market customers databases on our server.
  • Its ease of scale means auto balancing and reads by using replica sets.
  • It's cheaper in cost and depends upon RDBMS structure. It is platform independent and we can run on Linux as well
  • Its DB is schema-less if you want free and flexible table documents you should follow MongoDB so I recommend it
  • When one problem occurs we can't use joins and flexibility queries.
  • Data size in MongoDB is typically higher due to document failed names stored it.
  • It is not a great solution for performing a lot of writes when data size grows. It became lazy and we use other software to bring it back.
From my point of view when it uses joins then it can be used anywhere by anyone. We know it's built for clustering which means data is spread over multiple independent servers. If you need to load high amounts of data with a low business value then MongoDB is fine.
Wei Shan Ang | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
We used it as our main backend database for a particular platform within a department. It's very good for horizontal scalability. It allows us to scale out instead of scaling up. It is easy to tune and comes well-tuned out of the box. User bases are quite large as well.
  • sharding
  • replication
  • out of the box performance
  • maturity
  • documentations
  • WT stability
MongoDB is suitable for e-commerce level workloads. However, it is not very good in data warehousing workloads.
Jhonathan de Souza Soares | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is incredible. It solved a huge problem of performance inside of our APIs, including RESTFUL formating. It was very easy to scale and easy to manage the data inside the database.
  • Scalability
  • Durability
  • Easy to use
  • A little hard to find professionals to hire
  • Need to improve the UI IDE to manage data
  • Works better on Linux
  • Very good inside API scenarios.
  • Not so good for reports and aggregation of data.
September 12, 2017

Try MongoDB

Dipak Yadav | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
MongoDB is used to store non-relational data, i.e., user profile and application logs, it's being used by a specific project, it allows developers to work in an Agile way, and improve application's response time.
  • Storing/Retrieving Non-Relational , Hierarchical data & Geo Location data
  • Replication
  • Sharding
  • Improving MongoDB Connector
  • Making MongoDB Stitch to work with MongoDB CE
  • More Validation options at Document level
MongoDB is well suited for BigData and IoT applications.
September 12, 2017

MongoDB - A perspective

Score 10 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB in a testing environment to better understand popular NoSQL databases to be able to prepare our students for development positions.
  • Ease of use in application development.
  • Schema friendly design... it looks and acts like JSON objects developers are familiar with.
  • Excellent community of developers to assist with advanced configuration matters.
  • Server stats rely on command line interfaces with text output. Visualization is available through add on applications, but it would be great to have better native reporting.
MongoDB is well suited for almost all applications. The one area that it currently struggles with slightly is for transactional data processing.
Jeff Sherard | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
MongoDB is the main persistent datastore for our core platform. We had the opportunity to re-architect and re-home our platform (away from traditional RDBMS) on to a modern, cloud friendly, horizontally scalable, and highly available NoSQL database.

MongoDB is used at large scale, in large volume, and high transaction environments across the entire company.
  • Schemaless - make data changes on the fly
  • Document Based (aligns closely with object-oriented programming)
  • Built in DR and HA, scalable
  • Rich query language and aggregation tools
  • MongoDB is still a maturing platform. So it's a basic datastore - but advancing quickly and rapidly adding new features.
  • Search against a large database can be slow if not indexed properly. We use a caching layer (Elastic Search) in front of MongoDB for meta-data searches and then only search against MongoDB with very selective and targeted query (i.e. using _id)
  • It's a paradigm shift for users - to switch from thinking normalized and relational to thinking in documents.
Not everything is suited to a NoSQL database - but where it is, I would 100% recommend MongoDB where it is suited to the use case.
    • unstructured / schemaless data
    • large datasets that benefit from partitioning right 'out of the box'
    • devops culture
    • high availability environments that benefit from HA and DR right 'out of the box'

And recommend an RDBMS in other cases.
    • highly structured data
    • able to be normalized
    • strong relationships exist between entities
    • static, slow growth, small datasets
Score 6 out of 10
Vetted Review
Verified User
Incentivized
MongDB is used as a JSON document database for our organization and it's currently being implemented as we speak and it mainly addressed our speed problem.
  • Faster, more speed
  • Much more efficient
  • Pluggable storage engine API
  • Keep in mind if you're updating a user's social data that means going through all of the activity streams, which is error prone.
  • No backing of store behind cache means inconsistent data.
  • Not flexible with querying (i.e no JOIN).
Score 9 out of 10
Vetted Review
Verified User
Incentivized
I am a student. I have been using mongoDB in my academic projects and in my internship projects as well. I am pursuing my masters in software engineering and we use mongoDB entirely for every project that we do. In my internship at Ingram Micro Ltd. I did one project where the backend was on mongoDB.
  • Store metadata - Mongodb is best to use when we have to deal with a huge amount of metadata.
  • Scalability - MongoDB does scale well in comparison to other document specific databases.
  • Data handling - It manages data in documents.
  • It's a bit hard to learn and code using mongoDB.
  • No specific UI for management of a database.
It is well suited when you need ease of scalability. When you need more complex queries to query your database mongodb is less appropriate.
Joshua Austill | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use MongoDB to store analytics information from social networking sites, and also as our main datastore for our Intranet. It works well for both by providing very fast access to our data, and in a very simple way. All of our data is consumed by ASP.NET and used mainly in JavaScript, so working with documents is a very natural fit.
  • Replication, simplest replication I've ever had to set up, and it works very well.
  • Performance, because you are simply retrieving documents it is very fast. I've seen people try to use it like a relational system and have issues, but if you learn how it is intended to be used you will have very little concern with performance in my experience.
  • Maps to objects because it's BSON. Serializing is a major strength of MongoDB to me. It is pretty awesome to just grab a document and have an object in memory and away you go!
  • .Net driver implementation, I would like to see a driver that more closely aligns with the MongoDB way. Having to use tons and tons of helper classes to build queries is kind of a pain to me.
  • Recovery, it would be great to see ways to refresh replication and sharding settings once they are broken. The current path is to start over with new nodes and restore data. That could be improved in my opinion.
  • They don't include an init script for Mongo's service, which is really a shame to me.
I would say get familiar with the document model that MongoDB uses and apply it to your workload and see if it's a good fit. For most things web based I see it being a fantastic fit, the new features in 3.2 I think will make it pretty decent for analytics as well. I don't see it working great if you need your data extremely normalized and can't deal with documents however.
February 11, 2016

Great Document database

Score 8 out of 10
Vetted Review
Verified User
We're using MongoDB for a new pilot project. We want to use it in the future for more production projects. At the moment the main goal is to manage a transactional database for gaming using MongoDB and its main features like replica set and sharding and clusters and so on. It is the perfect database to do that because of its document store engine, that uses json documents and stored bson files. It's great for his schemaless structure and so on.
  • Schemaless
  • Sharding
  • Replica sets
  • Indexing
  • Performance
  • JSON
  • Of course there is no IDE, like SQL Server
  • Need some extra work to administer and set up
  • No sql, of course
MongoDB is well suited for document store, linear scalability and schema flexibility. The rich query and indexing functionality are great. No sql support, so it's not so appropriate for a "relational" software, which needs something like - for example- the support of a relational classic db like Sql Server, my sql and so on. A strong consistency model and open source does the rest.
Xunhui Yu | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB as back-end data storage for all of our different productions. First of all, it is easy for the programmer at the very beginning when starting the project because we do not need to do anything about "database design". It did a great job when the data increased quickly.
  • No database design
  • Viewable data record
  • Fast for scalable data
  • Client tools
  • More runable examples for map-reduce and aggregation frameworks
It is very good for social network user profile and other data which is not "well" constructed. The other reason it is suitable is the scalability, we have 10 million records incremented every day and it still runs perfectly even after we made about 10 shards. And the MongoDB backup solution is good too.
VenkataRamaRao Surapaneni | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Scaling the systems horizontally by distributing the load across the geographic systems both in on-prime as well as in cloud. improved the response times. provided support for our agile methodology software development life cycles with dynamic schema's, etc.
  • Horizontal and Veritical Scalling
  • High Availability, Disaster Recovery
  • High Durability and better response times
  • Easy to switch between servers with commodity hardware
  • Rich relational features like fuzzy logic, dataware house features
  • Easy monitoring and administration tools native with Mongo
  • Better election process by reducing downtime during elections
Durability, transactions (ACID), High availability & DR practices, scalability
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