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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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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.

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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

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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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(1-25 of 78)
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July 26, 2022

Why is MongoDB good

Mehmet Fatih Onal | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Due to the software developments made, the institution's NoSQL technology was needed. Therefore, a solution was created by purchasing the enterprise version.
  • We preferred the application because it stores documents in a JSON-like format. No need for extra format conversion.
  • Allows changes to the structure of documents and stores partially completed documents. The recorded data can be read very easily.
  • Can be user friendly. While it is very easy to create indexes in other database applications, it is a bit cumbersome to do this in Mongo.
  • The difficulties that we do not encounter when working with much larger data on MS SQL make us very difficult when working with fewer data in mongo due to the in-memory feature.
  • Since MSSQL does not have the unlock feature, it causes writing conflicts while reading and writing data at the same time.
If you are dealing with high-performance large volumes of data or if you want to add thousands of records in one second, MongoDB is the best choice for it. Since MongoDB is a schemaless database, horizontal scaling is very easy.
Kendal Droddy | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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.
Gaurav Pandey - PMP,ITIL,CSM | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Quick application development in the cloud in a no-SQL environment. For POC purposes, we sometimes are able to get free usage and also can evaluate the loads on the system which can be exploited to estimate real-time loads.
  • Storage of dynamic data from any source
  • Data agnostic
  • JSON-formatted data query
  • Max limit on document storage
  • No cross table joins
  • the backend architecture is complex and requires good understanding before developing the queries
1. Quickly scalable in cloud 2. This helps in rapid development because this is data agnostic and schemaless DB 3. No relational DB really helps for complex scenarios
Pablo Alejandro Laborde | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
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
January 17, 2022

Oleg's MongoDB review

Oleg Chumin | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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 scalable, and compared to traditional SQL systems, reads and writes much faster than SQL. What is done on Mongo is as simple and clear as possible, and if there are problems with the amount of data in relational databases, such “bicycles” will have to be invented that will reduce all the advantages of these databases to zero. It’s probably hard to do an initially limited project on ordinary relational databases, that is, not to think about what will happen when everything is slowly covered up ... It’s better to devote more time to the design of the initial data, which will remove all questions in the future.
  • MongoDB is highly scalable.
  • Reads and writes much faster than SQL.
  • What is done on Mongo is as simple and clear as possible.
  • Requirement from the application in a highly scalable database.
MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
Score 10 out of 10
Vetted Review
Verified User
This tool has been used project-wise for the projects in which real-time data is used for analysis. We use this tool for fetching the comments on the products on social media to understand the sentiments of the end-user. The data is real-time and unstructured so we use this tool to make our work easy.

Currently I am using it for storing and analyzing the live stream data. This works very fast and can be used by creating our own personal data types. We are taking huge volume of data for storage and processing made is very easy. Just connect and analyze it's that easy.
  • Reads real-time data very accurately and fast.
  • Syntax are so easy to learn and understand
  • Connection with the other tools through API's is also pretty simple.
  • Storing any type of data by creating personal data types.
  • Live streaming data processing is very fast.
  • Some basic statistical functions are there but we can apply high analytics models in it.
  • If the data is of similar type then it is very difficult to remove the same comments.
  • In the cloud environment sometimes it works very slow. Depends on the cloud source as well.
  • Sometimes it stucks, if columns are defined enough and data has some missing info as unstructured data can be of any type.
  • Sometimes very difficult to apply functions on the data types for that huge research is required.
This is a good tool in its category for reading real-time unstructured data. As my team works on understanding the sentiments of users over some products, initially we used SAS Text Miner but we were not getting those desired results as it was unable to process the real-time data.

The only major problem is that it is incapable of performing statistical analysis. Now as I am using it for streaming data for storage it working very much fine but some times if the logic is lengthy for defining data types then it will became tricky and hence then it becomes time consuming. Overall for unstructured data this tool will suits your requirement for sure.

Balázs Kiss | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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.
Score 9 out of 10
Vetted Review
Verified User
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 8 out of 10
Vetted Review
Verified User
MongoDB was our first NoSQL database usage. For this reason, we assigned it to an application that serves inside our IT infrastructure. As a result of our approximately 3-4 years of experience, we did not encounter any problems. It writes the data sent on it without any intervention and without any interruption, every second without stopping.
  • Flexible
  • Fast and easy to use
  • Open source
  • Free
  • İndexing is easy
  • No joins
  • Administrator GUI
  • Documentation can be more useful
  • Not ACID Compliant
We read data produced by a device in the network with a web API and take it on MongoDB. We also encrypt and compress text-weighted large data collected on MongoDB and extract it daily on a filing system. MongoDB preferred that for such applications because NoSQL structure gives more speed.
Score 10 out of 10
Vetted Review
Verified User
Used as a database solution for a web application for storing all data needed. That means all user details, application configuration and data created or managed by application's users is stored in MongoDB. It's used both by software developers for implementation purposes and also by support crew who maintain the application.
  • Simple structure, easy to understand how it works.
  • Easy to integrate with cloud providers.
  • Writing queries is easy to get started with.
  • When more complex queries are needed, they are more difficult to write than SQL equivalents.
  • Getting used to the aggregation framework takes some effort.
  • Upgrading between versions has required some additional work from developers in the past.
It's a rather obvious choice when a decision has been make to start a new project and ending up not wanting to implement it with a relational database solution. MongoDB is well suited in storing all kinds of data an application might need, all you need to do is evaluate whether the application would benefit from a relational database or not.
Score 9 out of 10
Vetted Review
Verified User
MongoDB is our primary database our application runs on. We use it intensively for our application development and data warehousing. I have used as a datawarehouse for analytics. It currently gets data from multiple dbs like mysql, app insights logs and other Mongo instances. I primarily use it for everyday metrics and analytics reporting
  • Robust and Out of the box DB
  • Mongo Compass Integration provides a sweet GUI for users
  • Well optimized No SQL DB
  • Great Community support
  • Sometimes queries are tricky to execute
If you are looking for a no sql db then MongoDB is one of the best open source solution with a great community who can help you to solve any problems. It has a high availability and indexing is pretty fast as well. You may have to research a bit on your use-case before going for a nosql db but if it fits your use-case then it is very developer friendly. Integrates well with nodejs, python , java etc.
Jose Manuel Ortega | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
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.
Score 10 out of 10
Vetted Review
Verified User
So this the non-relational Database that we have internally. The reason for using this is because of the amazing scalability that this database provides and the JSON file format in which it tends to store the data that is present within it. Its opensource and that is the reason we have been using it internally to store the git hashes of the manifest since there are millions of them getting generated every month and we need a method to scale to that extent.
  • NoSQL
  • Scalability
  • Readable queries
  • Opensource
  • None so far, but security issues have occurred
So if you need a highly available database, which you can rely on since it has inbuilt replication and JSON format message, then MongoDB is the best way to go for it. It follows BASE if the databases are inconsistent if you are scaling over a large system. What it means is that it is not suitable for storing passwords. For that, make sure that you use ACID databases which are relational.
Score 9 out of 10
Vetted Review
Verified User
We use MongoDB at the heart of our application where speed and consistency are critical. It's used primarily by the engineering backend team and vicariously by other teams using parts of the product. It gives us the means to quickly iterate our data models with fewer painful migrations than we'd have with a traditional RDBMS and its JSON-like BSON object modeling maps nicely to our APIs.
  • The BSON-based document storage models allow for sophisticated data modeling.
  • Flexible MongoDB collection schemas allow for the storage of polymorphic records and easy migrations.
  • MongoDB has readily adopted popular database concepts like change streams and graph queries.
  • MongoDB will start to struggle with very large datasets even when well-indexed.
  • Complex aggregation queries can be tricky in MongoDB when compared with an SQL-based database.
  • Scaling a Mongo database can be expensive.
Scenarios where MongoDB is well suited:
- When working with small/medium-sized dataset where speed and flexibility are priorities.
- When working with schema-less or polymorphic models that would be much harder to represent in a traditional RDBMS.
- More generally MongoDB makes sense as a place you'd store your business logic/frequently accessed data, not as storage for infrequently accessed long-term storage.

Scenarios where MongoDB is less appropriate:
- I wouldn't recommend using MongoDB as a caching service. It's more expensive than many databases that could be used where performance isn't a critical issue or long-term persistence is desired (e.g., compared with Datastore/Firestore/Dynamo/etc.), while it falls short of Redis when performance is critical or data need not be stored for long.
Gregory Pecqueur | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
We use MongoDB as a database for all web and mobile applications developed for our customers. It fully meets our needs. Reliable, handy, and robust, the support is of high quality. The installation on our servers is very easy. Its management and maintenance are easy and fast. MongoDB gives us satisfaction, and our customers are happy.
  • Mongo DB is free for commercial use
  • MongoDB is very fast for data processing.
  • Very easy to learn and use.
  • JSON responses are particularly handy in a full-stack Javascript environment.
  • A more user-friendly user management tool would be a good thing.
Modern web and mobile applications developed entirely in Javascript ( Node.js, Angular, or Vuejs or Emberjs.) are particularly interested in using MongoDB as a database. It is very easy to develop an API to manage the database accesses in an optimal, fast and secure way.
Loopback.js is a good starting point to get an idea of the potential of this environment.
Score 9 out of 10
Vetted Review
Verified User
Our Denver Development team is using MongoDB in an application they wrote, and it's collecting big data associated with the application's users. A SQL Server was formerly capturing this type of data and that's not a great platform for big data. They set it up, configured it, and got it working, all I have to do is the administration work required by SOX.
  • We're using it to capture/store big data
  • Easy setup and configuration by developers
  • The administrative interface isn't terrific, but it does work.
While we don't and wouldn't use it for transactional data, it's an excellent tool for collecting big unstructured data.
Russell Gomez | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
We use MongoDB as our main operational data store. The application writes directly to the database. We further use it to provide operational reports to our end-users.
  • Flexible schema for changing data elements.
  • Sharding and replication are seedless.
  • Setting triggers instead of change stream watcher.
  • Slowly changing dimension equivalent would be nice.
I believe any startup or any business with a rapidly changing data schema would benefit from using a no-SQL database in general. Analytical and traditional reporting can be difficult to do out of MongoDB or any no-SQL database because the SQL capacity is pretty limited.
February 26, 2020

Fast, easy to use!

Duncan Hernandez | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
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.
Gene Baker | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Using MongoDB as a potential solution for NoSQL data storage and quick application prototyping. It is an enterprise approved NoSQL solution. My investigation into the product and use of it is for innovation type activities.
  • Schema-less data models.
  • High performance.
  • Aggregation can be a little hard to learn.
MongoDB is very flexible, and high performing. I have evaluated a number of NoSQL databases and have found MongoDB to be the best overall. Aggregation pipelines took a little bit of practice to learn but once I got the hang of it, I realized how they could be used to solve problems easily.
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).
Thuvaragan Amarasingam | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
I am using it for my software development back-end system. All of my programmers also use this for the same reason. Its's very latest and efficient platform for developing applications. We can easily learn it from its official website and understand quickly. very easy query languages are available on this system. So we can access this.
  • Very easy query languages.
  • Less time needed to understand it.
  • Very easy installation.
  • Very fast for data inserting.
  • Transaction function not available.
  • Memory consumption is high.
MongoDB using JSON like documents in a database system. Also, it's an open source software. Its very flexible compared with other database related software. It helps to store a very large amount of data perfectly. It provides high performance, availability, and scalability. It's a NoSql database.

But the main disadvantage of this product is we can't use it for transaction functionalities.
Score 9 out of 10
Vetted Review
Verified User
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.
Score 10 out of 10
Vetted Review
Verified User
At my previous company, we had a mix of SQL and NoSQL databases powering our web platform. When building my new company, we made the decision early to go with a primarily NoSQL database solution. MongoDB powers our web platform, internal tools, and anything else we create. Working with MongoDB is painless and our developers love it - particularly Javascript developers, of which we have many, as we use a lot of Node.js. MongoDB makes development easy and production reliable.
  • Ease of use and familiarity, particularly for Javascript developers
  • Community, support, and tooling are readily available
  • Design with NoSQL in mind and you'll wonder why you ever needed relational features
  • Great query language
  • Complex querying. Aggregation could be better explained and a bit clearer
I think that MongoDB is the easiest and fastest database solution when starting any new project. Unless the project has a clear need for a relational setup from the beginning, it just feels a lot easier and faster to work with MongoDB. Scenarios where it's less appropriate would mostly be those that need the features of a relational (ex: SQL) database. Even then, we like to use MongoDB as a primary database and use SQL only for the aspects of the application that are better suited to it.
Sagiv Frankel | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
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 ( 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.
Score 9 out of 10
Vetted Review
Verified User
MongoDB is a solution for our company's NoSQL database. It is currently used by a few departments in our company. Our company needs to store millions of records and needs them to be written and read fairly quickly and MongoDB came into our sight as we looked for solutions. So far we have deployed one cluster and it processes millions of records every day.
  • Durability. MongoDB has a cluster structure ensures that data will endure without losing it. The primary-secondary-secondary structure is the key to preserve data.
  • Fast response. MongoDB responds to request in milliseconds which is very fast for data processing.
  • Price is fair. For the amount of money we spent, the product serves us well.
  • I understand the P-S-S structure is meant to be secure but sometimes I feel in some places it is redundant.
  • For more complex queries, it can be hard to work with.
  • The document is kind of not up to date.
If you have a large amount of unstructured data, (like NoSQL), to be read or written in a short amount of time, MongoDB is a great choice for this. Its structure well secures the data from being lost. It has good scalability to handle an increasing amount of data. It has a well-supported team to help you set up and maintain the cluster. Overall, it is a good choice to use for a NoSQL database.
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