MongoDB Reviews

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Score 8.2 out of 101

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Reviews (1-25 of 59)

Thuvaragan Amarasingam profile photo
Score 6 out of 10
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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.
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Chi Anh La profile photo
Score 9 out of 10
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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).
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Ronald Melendez profile photo
Score 9 out of 10
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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.
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Sagiv Frankel profile photo
Score 6 out of 10
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MongoDB was our main data store used primarily by a web application managing classical relational entities as well as some big data and analytics collection data. Even though no one on the team had much DB experience MongoDB was easy to use and integrate. However, we faced many pitfalls along the way and the end result was far from optimal.
  • Easy to set up locally and on different SAAS providers (Compose.io and then MongoDB atlas).
  • Being schema-less helped with having a rapid pace of development as there where many schema changes.
  • Full stack developers on a NodeJS server could get started very fast as the API was familiar and relatively simple.
  • Very hard to tell how to best structure your data and then effectively query it. Most of the time this led to just splitting everything into different collections and joining them on the application server or the client which was slow and hard to maintain.
  • Documentation is not friendly and confusing.
  • No real joins and complex querying is unclear.
MongoDB would be ok if you're starting from scratch with a very small team and want to gradually build your product (specification is in flux) along with continually learning, optimizing and monitoring your database (something one should probably be doing anyway). It also might be good if your system has little need for consistency and you can afford nesting documents and data duplication. For any other use case, like a big team with defined complex specifications or a high need for consistency, you will probably end up with a mess.
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Rounak Jangir profile photo
Score 9 out of 10
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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.
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Gabriel Samaroo profile photo
Score 10 out of 10
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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.
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Bill Hefty profile photo
Score 8 out of 10
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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.
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Miguelangel Nuñez profile photo
Score 9 out of 10
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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.
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Brett Knighton profile photo
Score 9 out of 10
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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.
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Score 9 out of 10
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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.
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Score 10 out of 10
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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.
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Score 9 out of 10
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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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Score 9 out of 10
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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.
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February 23, 2019

MongoDB Review

Score 8 out of 10
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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.
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Score 9 out of 10
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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.
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Score 7 out of 10
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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.
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Score 9 out of 10
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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.
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Joshua Weaver profile photo
Score 8 out of 10
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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.
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Nikita kumari profile photo
Score 9 out of 10
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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.
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Jon Kern profile photo
Score 10 out of 10
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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...
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Fernando Malave profile photo
Score 8 out of 10
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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.
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Sonaj Gupta profile photo
Score 9 out of 10
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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.
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Daniele Graziani profile photo
Score 10 out of 10
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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.
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Douglas Jagoda profile photo
Score 9 out of 10
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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.
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Jeff Sherard profile photo
Score 9 out of 10
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MongoDB is the main persistent datastore for our core platform. We had the opportunity to re-architect and re-home our platform (away from traditional RDBMS) on to a modern, cloud friendly, horizontally scalable, and highly available NoSQL database.

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

And recommend an RDBMS in other cases.
    • highly structured data
    • able to be normalized
    • strong relationships exist between entities
    • static, slow growth, small datasets
Read Jeff Sherard's full review

Feature Scorecard Summary

Performance (19)
8.8
Availability (19)
8.8
Concurrency (19)
8.4
Security (19)
8.3
Scalability (19)
8.8
Data model flexibility (19)
9.3
Deployment model flexibility (19)
8.8

About MongoDB

MongoDB (from "humongous") is an open source document-oriented database system developed and supported by 10gen. 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.

According to the vendor, organizations from cutting-edge startups to the largest companies use MongoDB to create applications never before possible at a fraction of the cost of legacy databases. The vendor says MongoDB is the fastest-growing database ecosystem, with over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.

MongoDB Features

Has featureComprehensive monitoring for full-performance visibility
Has featureAutomated database management for 10-20x more efficient ops
Has featureFully-managed backup for your peace of mind

MongoDB Screenshots

MongoDB Integrations

MongoDB Competitors

Pricing

Has featureFree Trial Available?Yes
Has featureFree or Freemium Version Available?Yes
Does not have featurePremium Consulting/Integration Services Available?No
Entry-level set up fee?No

MongoDB Technical Details

Deployment Types:SaaS
Operating Systems: Unspecified
Mobile Application:No