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https://dudodiprj2sv7.cloudfront.net/product-logos/x1/BQ/UA6NT9PUI691.PNGMongoDB is a great tool to read large amounts of data.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.,9,Reducing overall business costs as installation cost is very less of this tool. Less number of resources needs to maintain it. Quick and effective response to customers queries and issues.,MySQL, Visual Studio IDE, SoapUI NG Pro,8A NoSQL database for even the Non-data expertWe 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.,8,We didn't have to spend time and money on much training in learning database management It helped us get to market faster with a few different products We aren't pushing it to any limits yet so I can't give any hard numbers on performance or sharding stats.,Firestore,React, Mandrill, Mailgun, MailChimp, Nexmo, Google Drive,9,I like the javascript nature of the query syntax and API. Structuring data is just like structuring JSON. Some sophisticated reporting and querying can be done with relative ease with the Aggregate frameworks.,Relational data joins Normalized data (though the main usage pattern is to avoid this - sometimes it's hard to avoid, however) Structuring data for how you need to access it.,8MongoDB -- the "Honey Badger" of NoSQLWe 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 my time and money, I would start off almost every project using MongoDB -- even if I knew it might not be the ultimate final DBMS. Why? Because, in the early stages of product development, I am rapidly iterating on the domain, and other parts of the app. Sometimes changing my mind on major pieces of the architecture as we prototype early solutions. MongoDB works as freely and as quickly as I do. SQL databases do not. They get in the way, slow me down, tick me off. However, not all apps are well-suited for NOSQL. So if there are performance needs or other reasons that may point to SQL, then at some point I migrate. Controversial, I can imagine. But I could explain it over a beer. Or three.,10,Due to MongoDB's honey badger approach to persistence, it allows our teams to run fast at implementing our web apps. MongoDB is easy to administer -- especially because we use MongoDB Cloud to backup and monitoring. Admittedly we are not storing gazillions of documents (only 15GB), and we are not "pushing the envelope" on performance, so we do not require any database admins.,CouchDB, MySQL and Microsoft SQL Server,GitHub, IntelliJ IDEA,10If you want easy management and creation of database, MongoDB should be your choiceI 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.,Performance: MongoDB offers great performance when inserting data much greater than other traditional database systems. However, this advantage involves sacrificing characteristics of relational database systems such as the processing of transactions. Replication: MongoDB supports the type of master-slave replication. This replication system is simple to understand. Storage: MongoDB can be used with a file system, taking advantage of the capacity that MongoDB has for load balancing and data replication using multiple servers for file storage.,8,Infrastructure savings Hardware savings, since mongodb allows access to databases from the cloud. Easy access to thousands of data, quickly,,MySQL, SQLite, MariaDB,8,Yes,8,No,Once, I had a problem to pass a database to an older version. The MongoDB technical team explained to me step by step everything that I should do.It is open-source, cross-platform and schema-less.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.,Its file system, indexing to improve search and optimaizatio.i liked its BSON features because of all binary-encoded serialization. its create internally index and map document properties. BSON format is a use of the _id field as pk. it also supports ad-hoc queries by indexing and using a unique query language. It is schema-less as I mention in pros option.,9,investment for future return and profit increased productivity of business,my sql,MySQL, Microsoft SQL Server, HBase,8
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MongoDB Reviews

MongoDB
219 Ratings
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Nikita kumari profile photo
June 04, 2018

Review: "MongoDB is a great tool to read large amounts of data."

Score 9 out of 10
Vetted Review
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Review Source
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.
Read Nikita kumari's full review
Joshua Weaver profile photo
April 02, 2018

MongoDB Review: "A NoSQL database for even the Non-data expert"

Score 8 out of 10
Vetted Review
Verified User
Review Source
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.
Read Joshua Weaver's full review
Jon Kern profile photo
January 12, 2018

User Review: "MongoDB -- the "Honey Badger" of NoSQL"

Score 10 out of 10
Vetted Review
Verified User
Review Source
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...
Read Jon Kern's full review
Fernando Malave profile photo
February 13, 2018

Review: "If you want easy management and creation of database, MongoDB should be your choice"

Score 8 out of 10
Vetted Review
Verified User
Review Source
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.
Read Fernando Malave's full review
Sonaj Gupta profile photo
February 09, 2018

MongoDB Review: "It is open-source, cross-platform and schema-less."

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Sonaj Gupta's full review
Daniele Graziani profile photo
January 30, 2018

User Review: "I gotta have more MongoDB!"

Score 10 out of 10
Vetted Review
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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.
Read Daniele Graziani's full review
Douglas Jagoda profile photo
October 06, 2017

MongoDB Review: "I'm Liking What I'm Learning"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Douglas Jagoda's full review
Jeff Sherard profile photo
June 07, 2017

Review: "MongoDB underpins SaaS platform that drives billions of dollars in savings in healthcare..."

Score 9 out of 10
Vetted Review
Verified User
Review Source
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
Wei Shan Ang profile photo
September 15, 2017

MongoDB: "Review from a database agnostic user"

Score 6 out of 10
Vetted Review
Verified User
Review Source
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.
Read Wei Shan Ang's full review
Michael Höller profile photo
September 12, 2017

User Review: "MongoDB - the game changer"

Score 9 out of 10
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Verified User
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As a consultant I am working on our latest project as Solution Engineer and Dev Team Lead. MongoDB is used to save configuration data of any kind of device used in the scope of the company (a kind of CMDB). This data is structured by device, so in best case we can talk about semi structured data for a database perspective. To handle this it needs a flexible schema or a base set of relational tables surrounded be exception tables. Both would work to save the data. But when it comes to make use of it, the flexible schema of MongoDB pays dividends. Queries are much faster, and any adoption of a new device can be done with almost no impact, whereas we would need to define a further exception in the relational model.

Also the development turned out to be leaner since we could simplify the queries, and API.
  • Replication is a real plus; it is shipped out of the box and a simple three-node replication set can be setup with a few commands in less than 5 minutes.
  • Sharding steps in the same direction as replication, just more complex - what is in the nature of the issue since we are talking about distributed databases.
  • MonogDB is light and easy to run and administer
  • Monitoring is still a little bit difficult, though the latest releases of Compass (MongoDBs Monitoring tool) have led it to catch up.
Semi structured data. E.g collecting logs and events from machines or configuration data from various devices
Read Michael Höller's full review
Apnesh Sharma profile photo
September 21, 2017

MongoDB Review: "Awesome Product"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Apnesh Sharma's full review
Juan Antonio Roy Couto profile photo
September 21, 2017

"My fast review about MongoDB"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Juan Antonio Roy Couto's full review
Jhonathan de Souza Soares profile photo
September 14, 2017

Review: "MongoDB is the best NoSQL Document Model Database available in the market"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Jhonathan de Souza Soares's full review
Mauro Bennici profile photo
September 13, 2017

Review: "MongoDB to prototype JSON data ingestion"

Score 8 out of 10
Vetted Review
Verified User
Review Source
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!
Read Mauro Bennici's full review
Dipak Yadav profile photo
September 12, 2017

User Review: "Try MongoDB"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
Read Dipak Yadav's full review
Eddy Wong profile photo
May 18, 2017

User Review: "MongoDB is ideal for Startups"

Score 10 out of 10
Vetted Review
Verified User
Review Source
I am using MongoDB as a bread and butter database and main storage for our data objects.

In a previous opportunity, I used MongoDB to model graph constructs. Even though, MongoDB is not a graph db, I used its document oriented storage to store the adjacency list of a graph. Afterwards, I took advantage of its geo related features and indexing capabilities on date.
  • Model objects in JSON
  • Easy to get started, install and get going
  • Runs on my laptop (Mac) and can be easily scaled to Ubuntu servers
  • Ideal for startups, because it allows schema evolution
  • It's "write concern" was a flaw at the beginning
  • Authentication came later
  • It's aggregation language is not consistent, and sometimes difficult to get working
Mongo is well suited for startups because it is well suited for iterative development. You don't have to have a "schema" decided apriori. You can just dump your data and start querying it right away. Mongo is not very well suited transactional operations like purchases or checkouts.
Read Eddy Wong's full review
Devaraj Natarajan profile photo
August 31, 2017

MongoDB Review: "MongoExp"

Score 9 out of 10
Vetted Review
Verified User
Review Source
Currently, we use MongoDB for handling defect management for our company. There are several millions of unstructured records that come into the system and are queried by users. MongoDB handles these things smoothly. We build multiple dashboards and other metrics from MongoDB data, these are performed using simple find queries, aggregation, and MapReduce, they do the job seamlessly and smoothly.
  • Indexing
  • Sharding
  • Replication
  • Monitoring of Mongo infrastructure
MongoDB handled unstructured data very well.
Read Devaraj Natarajan's full review
Adrián Rivelli profile photo
August 02, 2017

User Review: "MongoDB for multiple purposes"

Score 9 out of 10
Vetted Review
Verified User
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I'm in charge of the database of the global department that sends all the alert notifications and statements for customers and we have a really intense use of the database. We store some customer information, rules and configuration for each product and country, and some of the content we send. We chose mongodb because of the horizontal scale out and the ability to work with complex structures of information.
  • Index creation: you can perform the process in rolling fashion, one server at a time avoiding performance issues or outages. In fact, a lot of maintenance task could do it this way.
  • Changing of the schema, we just deployed the new version of our new application, don't need to touch the database (in most cases).
  • Compression: the new storage engine (Wired Tiger) supports compression in a faster way.
  • JSON, once you know how to use it, it's a really good way to work with the database, I like it more than SQL, and it's really friendly with javascript, and node.js.
  • Well, I found some little differences between the behavior of mongodb and the documentation, (not related with a different version of the server)
I think is the best to work with the agile method because of the "schemaless" model and the horizontal scale out.
Now, with the new improvements, [its] a really good option for graphs and full-text search.
Read Adrián Rivelli's full review
No photo available
September 12, 2017

User Review: "MongoDB - A perspective"

Score 10 out of 10
Vetted Review
Verified User
Review Source
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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Niraj Adhikary profile photo
May 11, 2017

Review: "Wearable device development with MongoDB"

Score 8 out of 10
Vetted Review
Verified User
Review Source
MongoDB is used to store data for electric measurement (of an original product, a wearable device called puck for brain stimulation) as well to get users' feedback after usage. Our day-to-day work relies on MongoDB solely. You might be asking that's why did we use MongoDB at first instance! Well we were never sure of the volume of data that we will be dealing with. The amount of data we process right now is still very small(gigabyte only). But the story doesn't end here. We have an active replica set for our production. If the story makes a success we will be needed to create sharded cluster very soon. Hope so for now. As it happens now if we want to rewrite the whole code base we will be in a soup, MongoDB is so deeply integrated with all of our framework. Its the lifeline for our product and project.
  • Roll out new features in a timely manner: As we evolved from an experiment to a publicly available product, we saw MongoDB evolved with the same pace. Right now you can work with MongoDB with ease. Some people think it will take a huge amount of time to develop an application with MongoDB. But I can tell you the community has been growing and thriving. No need to get scared by relational databases anymore.
  • Strong support team: We had active support from MongoDB. I feel that was great. As I never had a ridiculous answer from the support team. They were always prompt, sharp and will have exact reasoning for the problem. The feature I like the most is virtually every language is supported by MongoDB for application development. Which made our job easier as a few developers and QAs were not accustomed to MongoDB.
  • New integration and frontiers: I feel the journey just started. With the Spark integration, MongoDB opens a new door for analytics which is great. We need more such features for analytics.
  • Reliability and durability: I replaced an existing replica set by a new one within few hours including data transfer. I don't know how fast it is for a relational database. I've never found any write or read failure of our production database. My application transfers data into megabytes to a mobile device within a few milliseconds, which is quite amazing.
  • Security and endured performance: With all our performance test results we are quite satisfied. The security is enhanced with https based communication among the replica set nodes. Even here you have user level access like a relational database but data can be grown much more than a relational database. With MongoDB, the performance we got was phenomenal and helped us to remove usage of the caching server.
  • Analytic: This area needs quite an overhaul with new features and integration. I think it has to be more thoughtful.
  • Migration: Needs hassle free migration from one version to the next or the previous. As of now, this feature is getting huge attention. Hope [they] will do better in future.
  • Query functions: Like RDBMS SQL functions are missing. Need to use aggregation framework for simple calculation, which is time taken and slow to run. Hope new functions will be added with new improvements.
  • Community driven features: Add more community driven features so that developers can write less code and do more.
MongoDB can be used in server based huge apps or for mobile apps supported by servers. In my present project, I'm using MongoDB for read-write operations done by mobile apps and web apps. Any app that generates a huge volume of data can be an ideal candidate for MongoDB. That shouldn't stop you from developing any sort of apps. I found no boundary of usage.
Read Niraj Adhikary's full review
Arnold Daniels profile photo
February 09, 2017

User Review: "MongoDB as bread-and-butter solution"

Score 9 out of 10
Vetted Review
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MongoDB is used as persistent storage for most applications and services of our organization. Because it's versatile it can be used for all general purpose cases. We only use a different solution if there is a clear benefit of a different database type, like an RDMS or key/value store. The dynamic schema makes working with MongoDB easy for the development team.
  • It is a mature project with good documentation and great support.
  • Querying the database is relatively easy compared to other NoSQL solutions.
  • A dynamic schema removes much of the DB migration issues to typically come with software updates.
  • MongoDB can be difficult to setup properly and manage.
  • The default settings are not secure. You need to actively configure the server for authentication and access control.
  • Good tooling is available, but relatively expensive compared to other open source products.
MongoDB can be used as general purpose data store ranging from small data sets to very large ones. It works especially well if you want a dynamic shema. Something a RDMS typically does poorly. With MongoDB you do need to consider how you want the query the DB in advance because you can't fetch related data from another collection. If that type of querying is important, a relational DB might be the better option.
Read Arnold Daniels's full review
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January 03, 2017

MongoDB: "Accelerate delivery with this general purpose NoSQL engine"

Score 9 out of 10
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MongoDB is used across the whole organization in several use cases. There are use cases which are utilizing the technology, for high-throughput, or high data volume on a level which may not be economical with different technologies, and there are others, which only would like to leverage the fast development cycle made possible by the dynamic-schema design.
  • High data volume low latency access.
  • Rich indexing and querying capabilities
  • Enterprise grade tooling. (Ops Manager, advanced Security)
  • There is no cross-cluster replication of any kind. That would be very useful in many cases, like disaster recovery or test data delivery to pre-production validation.
  • There is no multi-document transaction capability. This could be accepted with limitations like a transaction only on 1 shard.
  • Most of the tooling is closed source, and tends to be a bit buggy.
MongoDB is very well suited for use cases where the data volume and the throughput are higher than a traditional RDBMS could sustain, without the need for complex transactions. You can scale a single cluster to tens of TBs still maintaining low latency access. For thousands of concurrent requests, it is better suited for small short living requests, even with a large update volume. It is not a very good fit alone for analytical applications, as there are no QoS settings available and broken queries are not always recoverable or interruptable. Together with SPARK, for example, it can be a perfect solution.
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Tom Maiaroto profile photo
May 03, 2016

MongoDB Review: "Mongo Size Convenience With a Micro Size Learning Curve"

Score 9 out of 10
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Our engineering department uses MongoDB to power our SaaS. It stores data for our clients to create and configure assets for their account based marketing efforts including A/B testing and personalization.

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

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

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

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

MongoDB is less appropriate for time-series based data too.
Read Tom Maiaroto's full review
Joshua Austill profile photo
April 05, 2016

User Review: "I think MongoDB is great, so will you!"

Score 9 out of 10
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We use MongoDB to store analytics information from social networking sites, and also as our main datastore for our Intranet. It works well for both by providing very fast access to our data, and in a very simple way. All of our data is consumed by ASP.NET and used mainly in JavaScript, so working with documents is a very natural fit.
  • Replication, simplest replication I've ever had to set up, and it works very well.
  • Performance, because you are simply retrieving documents it is very fast. I've seen people try to use it like a relational system and have issues, but if you learn how it is intended to be used you will have very little concern with performance in my experience.
  • Maps to objects because it's BSON. Serializing is a major strength of MongoDB to me. It is pretty awesome to just grab a document and have an object in memory and away you go!
  • .Net driver implementation, I would like to see a driver that more closely aligns with the MongoDB way. Having to use tons and tons of helper classes to build queries is kind of a pain to me.
  • Recovery, it would be great to see ways to refresh replication and sharding settings once they are broken. The current path is to start over with new nodes and restore data. That could be improved in my opinion.
  • They don't include an init script for Mongo's service, which is really a shame to me.
I would say get familiar with the document model that MongoDB uses and apply it to your workload and see if it's a good fit. For most things web based I see it being a fantastic fit, the new features in 3.2 I think will make it pretty decent for analytics as well. I don't see it working great if you need your data extremely normalized and can't deal with documents however.
Read Joshua Austill's full review
Michael Grayson profile photo
March 23, 2016

User Review: "MongoDB: Great fit for many use cases"

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

Feature Scorecard Summary

Performance (2)
9.0
Availability (2)
8.5
Concurrency (2)
8.0
Security (2)
8.5
Scalability (2)
8.0
Data model flexibility (2)
8.5
Deployment model flexibility (2)
9.0

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