MongoDB Reviews

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Reviews (26-50 of 59)

Wei Shan Ang profile photo
Score 6 out of 10
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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

MongoDB - the game changer

Score 9 out of 10
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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

Awesome Product

Score 9 out of 10
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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
Score 9 out of 10
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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
Score 9 out of 10
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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
Score 8 out of 10
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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

Try MongoDB

Score 9 out of 10
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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
Score 10 out of 10
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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
Niraj Adhikary profile photo
Score 8 out of 10
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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
Devaraj Natarajan profile photo
August 31, 2017


Score 9 out of 10
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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
Score 9 out of 10
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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
Arnold Daniels profile photo
Score 9 out of 10
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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
Tom Maiaroto profile photo
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
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
Score 10 out of 10
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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
Amitendu Panja profile photo
Score 5 out of 10
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MongoDB was used to store middleware transaction messages. These JSON messages were sent across various heterogeneous systems like Maximo and Click Sycleo etc. It was only used to store the important messages for local use and references. The main system software IBM Maximo used a relational database. MongoDB was locally set up to store templates of frequent and different types of middleware messages.
  • Since Mongo DB stores unstructured data, it was easy to directly store messages in it. We did not have to de-serialize serialize the json data
  • Of bulk messages where exported from the Oracle Service bus which was the middleware into csv. The import of all the messages from the CSV and MongoDB was done using a single command
  • Complex queries can get confusing at times when comparing multiple constraints. The query language needs a bit of improvement.
  • Joins like mechanisms are missing in MongoDB.
As mentioned earlier MongoDB is very efficient for strong messages like JSON which are used to communicate between most webservices.
Read Amitendu Panja's full review
Fareed Abolhassani profile photo
Score 6 out of 10
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MongDB is used as a JSON document database for our organization and it's currently being implemented as we speak and it mainly addressed our speed problem.
  • Faster, more speed
  • Much more efficient
  • Pluggable storage engine API
  • Keep in mind if you're updating a user's social data that means going through all of the activity streams, which is error prone.
  • No backing of store behind cache means inconsistent data.
  • Not flexible with querying (i.e no JOIN).
Read Fareed Abolhassani's full review
Kamesh Ganesan, FLMI, PMP profile photo
Score 10 out of 10
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MongoDB is used across the organization. Since it's stored as JSON documents, it's used to store all our structured, semi-structured and unstructured data. The MongoDB database makes it easy to store and retrieve data. We use statistics and time series data in this database and it's very easy to project it in a graphical format.
  • MongoDB database uses the most widely used JSON documents to store and retrieve. Also it's stored as BSON internally.
  • MongoDB is well suited for semi-structured and un-structured data.
  • MongoDB is very easy to scale and replicate.
  • The possibility of using joins like relational databases.
  • Since it's storing key values in each document, it uses up more memory.
  • It also has concurrency issues for read and write operations.
  1. Schema-less design enables rapid deployment and enables the data store generic.
  2. Scale the application that already manages several TB in a single table, w/o being limited by adding new fields or being limited by growth
  3. Rapid replicaSet enables meeting regulation with easy to setup multi data center and HA solution.
  4. Sharding enables linear and scale out growth without running out of budget.
  5. MongoDB architecture is great for a system that must support high insert load.
  6. Developer oriented queries, enable developers write a elegant queries.
Read Kamesh Ganesan, FLMI, PMP's full review
Dror Asaf profile photo
Score 9 out of 10
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MongoDB is used as a database for our product in the health care industry, it is the persistence engine for real time analytics.
It is easy to use, allows us to focus on the product development process instead of the management of the database and the adaption of other third party tools which are related to the database.
  • Effortless sharding and scaling
  • High availability with almost no effort
  • Multiple drivers in the most common programming language
  • Extremely strong community
  • MongoDB on windows platform has some memory leaking issues
  • MongoDB works well only on specified file systems
  • No built in integration with cloud ops manager with Google cloud platform/ IBM Bluemix
The programming stack means, M is for mongodb which means it is part of the world wide new popular stack which is used as part of multiple web applications and websites.
Read Dror Asaf's full review
Ayush Choukse profile photo
Score 10 out of 10
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I am a Student at San Jose State University (SJSU) pursuing a masters degree in software engineering. I have used mongoDB extensively in every project since I have joined the college.
  • It scales well comparing to other DBs
  • It easy to learn and manipulate data using mongoDB
  • I am not an expert user right now in MongoDB. since I have know explored mongoDB to its core. So I don't think I would be able to comment on cons of MongoDB. So far I only had good experiences.
If you have data that is unstructured and has key-value pairs then you should definitely use mongoDB.
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Rekha Joshi profile photo
Score 8 out of 10
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MongoDB was used as a backend NoSQL document store on services which needed to work with JSON document files.
  • It is very simple to setup and quick to get started on, it becomes a developer's paradise.
  • It is the top NoSQL document store and provides consistency and partition tolerance. Works very well with JSON files.It has ease of shell interaction.
  • It supports clients on multiple languages.
  • It works well with Hadoop, Spark and Solr.
  • MongoDB is written mainly in C++ and Javascript. As Java is still the main language of developers, and Java 8 providing even the functional paradigm, MongoDB codebase and getting developer community around it can be a concern.
  • Understanding internals of MongoDB functionality can be a challenge due to the language barriers. It uses a specialized leader election algorithm, not standard Paxos or Raft consensus algorithm and this becomes a concern when trying to understand its internal functionality.
  • When I last evaluated it, it did not have best in class performance across different workloads.
  • The write performance needed improvement, but I hear Mongo 3.0 does has good performance on writes.
MongoDB is well suited as:

  • Highly performant processing and if your data model is mostly documents, this is a natural fit.
  • Ease of setup and simplicity of MongoDB interface remains much favored by developers.
  • Developers have a need to understand the internals, so if you have C++/javascript developers that is ideal.
  • If you really need relational database with ACID guarantees, you would need to use a relational database. But most use cases these days need often some set of features among them: consistency, partition tolerance and availability. MongoDB favors consistency and partition tolerance and most interactions/workloads have reasonably good performance with MongoDB.
  • It has great connectivity with Hadoop, Spark, Solr. This works in favor of MongoDB to be a part of your overall ecosystem.
Read Rekha Joshi's full review
Michael Plunkett profile photo
Score 7 out of 10
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I used MongoDB for a CRUD application that was used in specific train yard types throughout our system. The application runs 24/7 in multiple locations (2+) with database transactions happening probably once every 20 minutes at each location. The use of MongoDB addressed both getting me used to dealing with new technologies, as I was a new employee, and allowing me to easily manage JSON structures within a database (this applies since objects are stored in MongoDB in a similar fashion called BSON).
  • Since the bulk of our data structures were utilizing the JSON format, MongoDB was very easy to utilize.
  • Due to MongoDB's large presence in the software development industry, I was easily able to find a module for the framework (Play! 1.2.x) I was using on my specific project. The MongoDB plugin, Morphia, enabled me to seamlessly interface between my application and database with little to no complication.
  • The MongoDB tutorials are very well made, and simple to understand. This thorough documentation, in combination with their intuitive API, made dealing with any potential database modifications I had to make an absolute breeze to execute.
  • I was not personally able to find any means to automatically duplicate my MongoDB databases (after so many days, etc.) within the MongoDB API at the time I was using the product.
For me, it highly depends on the type of data structures you are dealing with. If your data is structured as JSON, or very similar, your project would likely benefit from the use of MongoDB. If you think of your data in terms of SQL tables, then I would not recommend the use of MongoDB. Using an object database demands a certain kind of design that I feel doesn't mesh perfectly with the SQL-oriented data.
Read Michael Plunkett's full review
Neerav Vyas profile photo
December 18, 2014

MongoDB for All!!!

Score 10 out of 10
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MongoDB is being used by my department and for 1 product only. People are learning about it's qualities slowly and hopefully will soon start to use it in other products. We had some scaling issues earlier with MongoDB and they have been resolved now. Also, there was a lot of debate about the sharding issue we had in Mongo database.
  • It is schemaless, so any type of data structure can be stored which makes it very flexible
  • Document embedding, which is alternate to table join in traditional DBs, works great
  • Sharding makes it really handy to access the data withing no time.
  • There is a limitation on the number of documents stored in a collection which can be better handled
  • A shard key cannot be changed after sharding a collection which makes it hard if we later decide to change keys on a collection
  • A database name in MongoDB can only be 64 characters long
MongoDB is very well suited for Content Management software where media is stored and served along with its metadata like in e-commerce, etc. Its also suitable for big data related applications like log data collections where effective storage, management and processing of large amounts of data is required. MongoDB fits the purpose in the above situations.
Read Neerav Vyas's full review
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September 12, 2017

MongoDB - A perspective

Score 10 out of 10
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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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David Lynch profile photo
Score 10 out of 10
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Since we're using the Meteor/Node.js "stack", MongoDB is a given (it is currently the only database supported by Meteor). I'm currently juggling three start-ups using Meteor/MongoDB. Two of them are SaaS start-up involving both websites and hand-held devices (multi-tenant/cloud), and one is a B2C website. MongoDB provides primary data storage for all three projects.
  • No schema. The flexibility is incredible, I'm still getting used to this coming from decades of experience with relational databases. MongoDB gives you incredible flexibility for modeling. By comparison, working with relational databases feels like wearing a straight-jacket.
  • Performance. One of our projects involves a MongoDB collection with tens of millions of records. Doing some tests on this, MongoDB doesn't seem to care, those supposedly "large" collections are nothing to this database. Given sufficient memory, Mongo will maintain most everything in memory and memory is now cheap.
  • JSON-friendly. Because the actual storage format closely matches the object format used by both client and server, there is no "impedance mismatch" which is a big problem with relational databases. This is a big topic so if you don't know the issue Google "impedance mismatch" to learn more.
  • The text-search feature is embryonic and needs some work. For technical reasons, text-search is done outside of the normal "find" mechanism used for traditional searches. This makes it tricky to use. It is also not possible to combine text with geo-spatial searches, which is something we need to do (we have to resort to two steps).
  • Triggers are not yet supported. Virtually all relational databases support this, and it would be handy if MongoDB did support triggers written in JavaScript. Note that for us, this isn't a show stopper since our Meteor/Node.js system has support functionally-equivalent to triggers.
MongoDB is perfect for SaaS projects with loosely-structured data (think Facebook or Twitter). It is less valuable in situations that require "life-and-death" transaction control (e.g., financial balances) where relational databases still have advantages. MongoDB is open source, so we haven't really had to interact with the vendor per se. Most answers can be found quickly by Googling.
Read David Lynch's full review

Feature Scorecard Summary

Performance (19)
Availability (19)
Concurrency (19)
Security (19)
Scalability (19)
Data model flexibility (19)
Deployment model flexibility (19)

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


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