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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

(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

(26-50 of 78)
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Score 9 out of 10
Vetted Review
Verified User
Incentivized
Mongo DB is an incredible storage software with a huge database designed for Powerful, easy and intuitive documents. We are using Mongo DB in our team for the Messaging system. Being the Messaging system, it has to find subscribers and send them messages fast. The best thing is to have software that allows you a better development in your area of work. Mongo DB offers the best tool to carry out all our goals.
  • As Mongo DB is free for commercial use, it helps in creating the startup from scratch and hit the ground running.
  • It makes messaging system management easy on cloud. Mongo DB helps to manage db on cloud.
  • Mongo DB should return valid error while using JSON schema. It is confusing if error is not shown properly.
  • Support for MongoDB should be improved.
In case if you have less budget, go for this tool as it's free. Also, if you want to work with JSON Schema or file system, I will recommend this tool. In case budget is not concern, I will recommend SQL server or OracleDB.
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.
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
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.
Gabriel Samaroo | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
The Engineering team uses MongoDB as our NoSQL database technology. While we do use a relational database (MySQL) as the primary data warehouse solution, we use Mongo for specific data sources that are very unstructured. The effectiveness of Mongo on schema-less data makes it a great tool for us because accomplishing the same things we do in Mongo in MySQL would take longer and be far less performant.
  • Very easy to learn and use. Arguably a simpler query language than traditional SQL.
  • Large community and excellent documentation. This means many resources and support available.
  • Great for dealing with unstructured data. No need to spend time creating schemas (when unnecessary).
  • Cost efficient. Free for many types of use.
  • Less flexible than traditional SQL (i.e.: no joins). This means it's not suitable for certain data needs.
  • Can take up more space than typical relational DB, which can be problematic for very large data warehouses.
  • Not fully transactional (ACID compliant).
If you need a database that can store and handle unstructured data very easily and that is performant, MongoDB is a great solution. It is very easy to set up and has a large community of users. Mongo can integrate with all of the major languages (ie: Java, Python, etc.). If you need to store very complex, structured data that needs to be related, a traditional relational DB might be a better option.
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.
Bill Hefty | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I have used MongoDB as the database of choice for a NoSQL implementation for various apps. Implantation with Node.JS and Express is very seamless and easy, particularly when using Mongoose. Dealing with a document based solution for a database makes it pretty easy to use in a full stack Javascript app without needing to flip mindsets.
  • Easy to run locally on a dev machine
  • Easy to integrate into a schema model via Mongoose
  • Document-based storage makes it easy to work within a full stack Javascript environment
  • Getting MongoDB installed locally can be a challenge
  • The CLI can be kind of confusing for beginners, but MongoDB Compass makes up for that
It is very easy to get started using MongoDB, and getting a data schema created via Mongoose if using Node.JS is pretty simple as well. For small beginner projects, something like Firebase may be easier to get running and simpler to deal with for reads/writes, but for more advanced control and a more structured approach, MongoDB is a great solution.
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.
Brett Knighton | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
For a few years now our company has been replacing some very expensive Oracle DB's with much less expensive and lightweight combination of MongoDB with Elastic Search assisted collections. We have some extremely data heavy collections that used to take upwards of 30 seconds to search. With only Mongo collections and not having a normalized database I think we would have seen improvements, however, using Mongo in conjunction with Elastic has allowed us to make similar and more complex queries in fractions of a second.
  • Easy to set up in AWS.
  • Easy to scale. If you're worried about growth while maintaining consistent performance adding nodes is easy.
  • Mongo typically will typically require more storage space for the "same" amount of data stored in a normalized database.
  • Many features of other popular databases aren't available in Mongo such as Joins and Transactions.
This really comes down to need. I would have to look at the specific use case and decide if Mongo would be a good recommendation. Mongo does a lot of things really well, is easy to work with, and has fantastic documentation. However if transactions for example were a requirement within you application I wouldn't be able to recommend Mongo.
Nikita kumari | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
MongoDB using to store all clients info and their invoices and settlement info. This also used to keep a record of customers queries and frequently asked questions by customers.
  • The schema-less feature really makes it easier to use.
  • As we know this is free and it allows to run queries on Linux as well.
  • Data retrieving is faster than other databases.
  • It provides less flexibilty while writing complex queries.
  • It should support multiple document level.
  • This takes higher size to store data.
If we want to avoid complex schema this tool is best as we do not need to create databases schemas. This tool also reduces the overall reads performance ad it works with replica sets.
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.
Fernando Malave | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I work in the informatics department. We currently manage the databases of some banks in my country and the employees of the IBM branch in Venezuela. I believe that it facilitates the management of a large amount of information, which is why bank branches choose us as their operators.
  • Unlike relational databases, NoSQL databases are based on key-value pairs. MongoDB is the major NoSQL database.
  • Some types of NoSQL database stores include column stores, document stores, key values, graphics, objects, XML, and other data warehouse modes.
  • The interface is a little complicated to learn.
  • They could improve compatibility with other NoSQL databases.
  • I have had problems with data relationships when information is very large.
For databases that involve storage by document folders, MongoDB is ideal. Now, if a very large database is required, MongoDB can have problems because it is more complicated to call the data to avoid having to spend hours looking for them.
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.
Daniele Graziani | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
We use MongoDB to power our new e-commerce platform. The first feature that we have enabled has been the product catalog search. Thanks to 3.6 change streams we are able to react when a user searches and there are no results. We can even send a text message through Stitch/Twilio integration to send a personal message to the user.
  • MongoDB offers Stitch, which can replace a lot of backend code through its API. It can also integrate your application with a lot of services such as Twilio.
  • Change Streams allow you to create responsive applications.
  • The BI Connector has been redesigned and it has become a lot faster to set up.
  • Stitch is still in Beta. A few features are still not available. I expect those features to be available in 2018 sometime. Example features missing are Change Streams and $text.
If you just need a key-value pair you can use Redis. But, in my opinion, MongoDB can do it all today and will blow your mind in the future.
Jon Kern | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
We are using MongoDB as the backbone of our latest product offering, the Project Portal (v0.9 released Jan 2016). This is a Saas offering that we essentially white-label to our OEM clients for their customers and end users. MongoDB offers a robust, scalable, simple-to-get-started solution for the persistence layer of our Rails app.
  • As a software architect, I like the ease with which MongoDB avoids the typical "impedance mismatch" between traditional SQL and the object-oriented problem domain classes. MongoDB (via mongoid) in our Rails app is like a "hot knife through butter." It is much more akin to an OODBMS than anything else.
  • MongoDB is easy to use throughout product development as it is the "honey badger" of databases. As your product rapidly goes from idea to startup to scaling, MongoDB makes it easier than any SQL database I ever used. You spend more time building your solution, and less time worrying about feeding, nurturing, and migrating the SQL beast.
  • The ease with which you can spin up replica sets is amazing. No more excuses that you could not build a robust persistence layer. (Especially if you tack on services like MongoDB cloud offerings.)
  • I also take advantage of the geo-aware spatial indexing. To be able to geocode users, logins, problem domain classes (entities with an address), and do geo-aware queries -- like find me all of the X within Y miles of point Z. Booyah!
  • I love the idea of Map-Reduce native support in MongoDB. Admittedly I have not used it as much as I would like -- it always seems to trip me up.
  • Recent additions to the aggregation queries have helped reduce (no pun intended) my need to better wield the weapon that is Map-Reduce.
For most every basic web app that I have developed, MongoDB is well suited. I find it hard to imagine scenarios where it would not be...For apps where we have dynamic, user-controlled attributes, MongoDB makes this really easy. I would imagine MongoDB might be least appropriate for teams not interested in trying to learn a NoSQL approach. Try a skunkworks project then...
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.
September 21, 2017

Awesome Product

Apnesh Sharma | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
It's an awesome product. I started work with it 10 months ago. It is a very original, flexible, and attractive product.

It is a document database in which one collection holds different documents. The number of fields, and content and size of the documents can differ from one document to another.
  • It is schema-less
  • Faster turnaround in development
  • MongoDB has the best features of key/ value stores, document databases and relational databases in one
  • Trigger function
  • Max BSON document size is 16MB
  • Mongo provides GridFS to get around this , No more than 100 levels of nesting
It is schema-less and provides faster turnaround in development. MongoDB has the best features of key / values store document databases, and relational databases, all in one. Maintenance and upgrades with good functionality are a plus.
Cons: There is no trigger function, and the maximum BSON document size is 16MB. Mongo provides GridFS to get around this, but with no more than 100 levels of nesting.
Juan Antonio Roy Couto | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use MongoDB across the whole organization. It allows us to develop internal applications and, also, apps for other companies.
  • Failover
  • Scalability
  • High availability
  • Speed
  • Replication
  • Balancing
  • Text search
MongoDB is a general purpose database, so it fits very well in a lot of scenarios, even in event sourcing or time series.
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.
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!
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.
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