Skip to main content
TrustRadius
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…

Read more
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 …
Continue reading

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 …
Continue reading

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 …
Continue reading

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 …
Continue reading
Read all reviews

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%
Return to navigation

Pricing

View all pricing

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
Return to navigation

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
Return to navigation

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
Return to navigation

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).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(432)

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

(1-13 of 13)
Companies can't remove reviews or game the system. Here's why
Score 9 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is one of the main databases we use for our SaaS product. Its flexibility and ease to develop with allows our development team to quickly prototype and validate new product ideas, allowing us to bring new features to the market at a much faster speed.
  • Scaling and replication.
  • Easy to develop with.
  • Good support by many cloud vendors.
  • Good tool support, such as MongoDB Compass.
  • Query becomes more complex when your data starts to have relations.
  • The aggregation framework has a bit of learning curve.
  • Being schema-less can sometimes lead to bad data modeling designs.
  • If you need to change the name of an attribute (i.e. column name of a table for SQL), it can become tricky.
If your use case does not require relation heavy data models or transactions that need to be ACID compliant, MongoDB can be a good option, especially if you are starting with a new project and need to prototype and validate your ideas quickly. Its schemaless design allows you to change your data models on the fly, which can often be the case for new projects. However, the key thing is making sure your developers can get their heads around how MongoDB works and the lack of SQL.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB in one of our major user facing applications designed to showcase the results and analysis of students' assessments. This portal is very complex and contains various views of similar data across different dimensions. MongoDB is used as the underlying DB to help us store and retrieve the myriad data ingested via different sources for our B2B reporting. It addresses one of the major issues of non-relational, async, hierarchical data structure of our streaming data source.

We also use it for few of our other business facing apps as well. They are all independent custom built apps using different front-end technologies.
  • Extremely fast reads and writes if using the right indexes
  • Built-in aggregation function for on-demand computations
  • Ability to use any cloud provider for implementation. Even their own Atlas service is pretty good and affordable.
  • If installing it on-prep or on your own account in a public cloud, it can be a daunting experience.
  • Their aggregation functions still have room for improvement.
  • Native operational reporting functionality is a bit quirky and you have to pay for it separately. This should come built in and free.
This product is well suited if your need is to use a fast distributed DB with semi structured data and your semantics are not well predefined. It's also useful for building apps requiring real-time responses and fast deployment with ease of maintenance.
I wouldn't recommend you use it for any scenarios where it's beneficial to normalize the data.
Sagiv Frankel | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
Incentivized
MongoDB was our main data store used primarily by a web application managing classical relational entities as well as some big data and analytics collection data. Even though no one on the team had much DB experience MongoDB was easy to use and integrate. However, we faced many pitfalls along the way and the end result was far from optimal.
  • Easy to set up locally and on different SAAS providers (Compose.io and then MongoDB atlas).
  • Being schema-less helped with having a rapid pace of development as there where many schema changes.
  • Full stack developers on a NodeJS server could get started very fast as the API was familiar and relatively simple.
  • Very hard to tell how to best structure your data and then effectively query it. Most of the time this led to just splitting everything into different collections and joining them on the application server or the client which was slow and hard to maintain.
  • Documentation is not friendly and confusing.
  • No real joins and complex querying is unclear.
MongoDB would be ok if you're starting from scratch with a very small team and want to gradually build your product (specification is in flux) along with continually learning, optimizing and monitoring your database (something one should probably be doing anyway). It also might be good if your system has little need for consistency and you can afford nesting documents and data duplication. For any other use case, like a big team with defined complex specifications or a high need for consistency, you will probably end up with a mess.
Rounak Jangir | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We are using this database to store the raw JSON data as documents. We are using this to store the user's activity as a row in JSON so that we can later process that data. This tool is not being used by everyone in the company, but only a few of us.
  • Good integration with the Hadoop ecosystem, so it can be used with the other services of the Hadoop ecosystem.
  • A good NoSQL family database, so you can easily store the raw data as documents.
  • Good scalability as you can easily share the data and have quick availability of data.
  • Easy replication of the data.
  • Learning will definitely take time.
  • Updating is not fast, so if you have a use case where you need to update your data at a high rate, then it is not a good choice
MongoDB is very much well suited if you are storing raw data. Also, it can be easily integrated into the Hadoop big data ecosystem, so it is useful if you have a large amount of data. Scalability is another amazing feature of this database system. But MongoDB will not perform well if you have a use case where you have to update your data very frequently. In case of frequent updates, Cassandra will be a better option.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
My company is a non-profit healthcare delivery institute, and has been conducting a number of data science/advanced analytics projects collaboratively with other healthcare and research organizations. We had an experience with using MongoDB for a recent big data project with a university that stores genomic sequencing data in a non-SQL database, and developed a web-based visualization tool presenting phenotype patterns based on the data.
  • It is basically a well known and popularly used non-SQL database. It provides great performance, especially when reading big sized document or text (such as sequencing), well-developed functions, and online support.
  • There are many database developers who are already familiar with MongoDB, like other major non-SQL products. It is easy to hire engineers with reasonable payment.
  • Since our project was genomics research, we handled tables with numerous rows and large file size. MongoDB was performing well in hard conditions and very stable.
  • There is no JOIN and TRANSACTION, so it was required to add those by application developers. It was mandatory for us to do it since we had to merge genomics data in MongoDB with RDBS based clinical data.
  • MongoDB doesn't provide good data wrangling functionalities, such as parsing JSON or XML.
  • Data type definition in MongoDB is somewhat different than other databases, and results in some learning curves for our DB and app developers.
MongoDB is a well developed, commercialized product. There are other products which can be good choices, but MongoDB is a safe choice since it was already validated in the market by many customers. Which means, for any general purpose, it will fit in to some extent. In our project, the problem was extensibility to larger scaled genomics information that may require big data management functions. MongoDB is excellent when it is for a small project, but it is also well supported as the project and size of data to be managed grow.
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.
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.
Joshua Weaver | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We utilize MongoDB for both an internal custom CRM that handles our day to day operations and also in some of our products that are currently in service. We also have some apps in development that are yet to launch which use it. MongoDB is a fast and efficient NoSQL data layer for our web apps that allows us to be flexible and iterative with our development.
  • Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
  • Fast performance.
  • It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
  • There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
  • Query syntax is pretty simple to grasp and utilize.
  • Aggregate functions are powerful.
  • Scaling options.
  • Documentation is quite good and versioned for each release.
  • An aggregate pipeline can be a bit overwhelming as a newcomer.
  • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
  • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
If you are a small development company or don't have access to experienced DBA folks, MongoDB can be a good choice for the developer to take the data by the horns.
MongoDB is easy to handle when it comes to migrations because of its schemaless nature.
It can help you get to market faster because you're not spending a ton of time with dev ops and organizing data structures. You can iterate pretty easily. I would say it's a good choice for most web apps, but you might run into restrictions on certain data queries that MongoDB just can't do as efficiently as a relational database.
It can also be hard for some folks coming from a relational data model background. The idea of denormalized or redundant data can feel dirty to some. But the speed and performance in development and execution appear to make up for those faults.
Douglas Jagoda | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
MongoDB is being used as a free-flowing document store for tax information.
  • Allows for free-flowing attributes
  • Scales easily
  • Improving with each release
  • Re-sharding can be cumbersome
If you have a dataset that is not always consistent, consider storing it in MongoDB. If your data is normalized, it may not be the best solution.
Mauro Bennici | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use MondoDB at You Are My Guide to fast prototype the ingestion of new API. The possibility to save, update and search documents in JSON format allow as to save the useless time waste to convert data from SQL structure to JSON and vice versa. We use it in C#, python and GO without any problems in Windows, Mac and Ubuntu.
  • Easy to install and manage.
  • Ready in 10 minutes.
  • Query language is easy to learn.
  • Multi platform.
  • Missing official GUI (now we are [using] Compass).
  • Import and Export of huge amount of data is too slow.
When the needs are to insert, update and search JSON documents, MongoDB is the database!
Tom Maiaroto | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Our engineering department uses MongoDB to power our SaaS. It stores data for our clients to create and configure assets for their account based marketing efforts including A/B testing and personalization.

The configurations for these assets can get fairly complex and contain nested structures. A document store is ideal for this type of data and MongoDB makes it a breeze. Data is needed in web browsers as well, so having native JSON support is very convenient and valuable to us.

Our dashboard features reports for our users and once again MongoDB supports our complex reports using its aggregation framework.

MongoDB's replication has helped our application easily scale to support many clients.
  • Document object storage. JSON (BSON) native with JSON query syntax makes things familiar for JavaScript developers.
  • Generating aggregate reports using the aggregation framework is extremely convenient for analytics and reporting. It saves time.
  • MongoDB scales nicely. Replica sets are easy to bring online and help solve throughout issues for read heavy applications.
  • MongoDB's auto-sharding is fairly easy and helps solve issues for scale when it comes to writing lots of data.
  • When working with large data sets that benefit from many indexes (reads), it can slow down writes.
  • MongoDB is simple to use, but deceptively difficult to master for performance. More documentation around some pitfalls would be great (though there is some and more than there once was, it is improving).
  • MongoDB now has V8, but still runs many operations in a single-threaded capacity. It could be faster for certain tasks.
  • Depending on what's going on, replication lag can be slow and can cause problems.
MongoDB is well suited for development speed. It helps teams work with data quickly and the learning curve isn't very steep as compared to SQL queries. It's far more user friendly for both back-end and front-end developer alike.

MongoDB is less appropriate for e-commerce and micro-transaction applications where SQL transactions are of far more benefit. However, it is certainly possible to build e-commerce sites with MongoDB. It has been done. It's just perhaps a little less appropriate.

MongoDB is less appropriate for time-series based data too.
Michael Grayson | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
MongoDB is being used here to support a use case where a relational DB fails miserably. The data for this use case varies by municipality, state, region, country, etc., so there's hundreds of variances between one piece of data and the next. In a relational DB this would need to be managed by either multiple tables, or a table with a very large amount of columns which quickly becomes unwieldy when indexes are added to the mix. With MongoDB we're able to store all this data together, index it appropriately and retrieve it more quickly.
  • MongoDB handles variable data extremely well and allows for extremely fast retrieval and processing.
  • Since MongoDB natively supports JSON it has made development extremely quick.
  • MongoDB Operations are very simple and allowed us to operationalize it very quickly.
  • MongoDB does not currently support ACID Transactions, they are looking to tackle this issue in their next release.
  • MongoDB's query language requires a learning curve for those in the relational world.
  • MongoDB does not natively support SQL.
There are many scenarios where you should use a relational database. MongoDB does not fit every use case, please keep that in mind. Don't try to fit a highly relational data model into MongoDB, it might work, but the performance issues will inevitably come shortly after. If the data is variable and not relational, MongoDB is a great fit.
December 18, 2014

MongoDB for All!!!

Neerav Vyas | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
MongoDB is being used by my department and for 1 product only. People are learning about it's qualities slowly and hopefully will soon start to use it in other products. We had some scaling issues earlier with MongoDB and they have been resolved now. Also, there was a lot of debate about the sharding issue we had in Mongo database.
  • It is schemaless, so any type of data structure can be stored which makes it very flexible
  • Document embedding, which is alternate to table join in traditional DBs, works great
  • Sharding makes it really handy to access the data withing no time.
  • There is a limitation on the number of documents stored in a collection which can be better handled
  • A shard key cannot be changed after sharding a collection which makes it hard if we later decide to change keys on a collection
  • A database name in MongoDB can only be 64 characters long
MongoDB is very well suited for Content Management software where media is stored and served along with its metadata like in e-commerce, etc. Its also suitable for big data related applications like log data collections where effective storage, management and processing of large amounts of data is required. MongoDB fits the purpose in the above situations.
Return to navigation