TrustRadius Insights for MongoDB are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Business Problems Solved
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.
We use MongoDB to store invoices data, like total, items included, date. we use it to store and read data from it via an API with fast API and that's it. so far we have had zero problems.
Pros
Perfomance
Store unstructured data
Integration with python connector.
Likelihood to Recommend
Its perfect when you want to store data that is not always in the same format or that data may vary, or change format.
VU
Verified User
Professional in Information Technology (51-200 employees)
Due to the software developments made, the institution's NoSQL technology was needed. Therefore, a solution was created by purchasing the enterprise version.
Pros
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.
Cons
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.
Likelihood to Recommend
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.
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.
Pros
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.
Cons
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.
Likelihood to Recommend
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.
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.
Pros
Storage of dynamic data from any source
Data agnostic
JSON-formatted data query
Cons
Max limit on document storage
No cross table joins
the backend architecture is complex and requires good understanding before developing the queries
Likelihood to Recommend
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
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.
Pros
Scalability
High Availability
Easy to install
Free training
Cons
Offices in south america to provide more sales markets
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.
Pros
MongoDB is highly scalable.
Reads and writes much faster than SQL.
What is done on Mongo is as simple and clear as possible.
Cons
Requirement from the application in a highly scalable database.
Likelihood to Recommend
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.
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.
Pros
Scaling and replication.
Easy to develop with.
Good support by many cloud vendors.
Good tool support, such as MongoDB Compass.
Cons
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.
Likelihood to Recommend
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.
VU
Verified User
Employee in Information Technology (1-10 employees)
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.
Pros
Flexible
Fast and easy to use
Open source
Free
İndexing is easy
Cons
No joins
Administrator GUI
Documentation can be more useful
Not ACID Compliant
Likelihood to Recommend
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.
VU
Verified User
Professional in Information Technology (1001-5000 employees)
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.
Pros
Simple structure, easy to understand how it works.
Easy to integrate with cloud providers.
Writing queries is easy to get started with.
Cons
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.
Likelihood to Recommend
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.
VU
Verified User
Employee in Information Technology (1001-5000 employees)
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
Pros
Robust and Out of the box DB
Mongo Compass Integration provides a sweet GUI for users
Well optimized No SQL DB
Great Community support
Cons
Sometimes queries are tricky to execute
Likelihood to Recommend
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.
VU
Verified User
Employee in Information Technology (1-10 employees)
