MongoDB Reviews & Product Details

Horizontal scale out and schemaless are the best

Sometimes the error messages are not clear enough and you need to investigate in deep to found the root couse of the problem

Index creation on each server separately without affecting performance

Very easy to learn the concepts Easy to install (for a single node) A lot of programming languages to query the database Many tools (Robomongo is good one)

Complexity of the architecture when you deploy a complete solution with sharding and replica set

With such as schema free solution of datastore, you can make quick evolutions of your application without too much technical constraints. All developers become rapidly competent to evolve the applications. Major benefit: it reduces the time to market : from the idea to the deployment in production, it can be a question of hours !

Ease of use, great customer experience. builds the runway for growth.

New information is available only in the seminar's sessions

Customer Experience , Agility and Growth

The ease of the install process and the speed of the processing of data is unmatched by other databases on the market today,

Support at times is a little difficult at times. Being an enterprise customer, I would like to see an enterprise support dedicated phone number to call for live realtime support and assistance.

We were able to reduce latency that we were seeing with our older configuration using SQL. Mongo was able to reduce our costs by not have major license or larger carbon footprint.

Easy to implement, Stream line product , best support.

Corporate IT need

Telematics--realized that MongoDB is great for iterating quickly

The key factors that I like are the flexible schema and easy integration with many languages.

Until recently, scaling and clustering have been fairly painful to manage. The query language is flexible and expressive, but it does require s bit of a learning curve.

Simplifying the data model and access mechanisms for data.

Contrary to relational DB, MongoDB gives great features in upcoming 3.6 for business users to do preliminary data analysis and its connector with R may be a great help for Data Scientists for Hypothesis testing and model building

I don't dislike anything as such. It is a great product

Content Monetization applications using MongoDB is a great way we are leveraging the product.

It is very easy to use and has great driver nuget packages. Very scaleable and Highly available

It is taking our infrastructure teams a long time to get setup but that is most likely their fault and not mongos.

Highly scaleable and high volume database interactions.

It's very usefull and easy to use. JSON documents are easy to read.

Not listed in linux repositories by default

Significantly increase the speed of queries' response to previous version in sql.

- Ease of use - Easy to become productive - Easy indexing - Easy to install - Query language - Easy to scale - I was able to implement a polyglot solution combining MongoDB and Neo4j, a graphdb. The architecture has not fundamentally changed since (Aug 2013) and we now serve over 1 million users a month. And we have a lot spare room to grow with, with no major db changes. Our solution has scaled period, could not have done it with a relational db.

- Initial write issues in early version - Concurrency limitations

- Creating a startup from scratch and hit the ground running - No need to manage schema migrations, which would have hindrance our speed - Solved the problem of search in the bus and train industry, we've been a pioneer in the field. We have build an entire platform that standardizes the access of bus and train information.

DB data structure and scaling features at first, data modelling , normalization and schema practices known for it data storage practices, and its recent releases 3.4 where it offers views, graph traversal

Currency and Timezone point of effort needed

product database

Free to add or change fields Fast performance Compression (starting with WT)

w=0, default handling in earlier versions in earlier versions, the disk usage was quite high (about 10x the actual size)

Storing session data Analytics

Easy to use, but still require a little reading up before able to put to use. Able to search for specific usage relatively easy on the web. Stays out of the way of developers attention

Nothing I do not like so far. If anything, you can improve the preformance

A mySQL replacement. MongoDB delivers and improve my speed of delivery

Very flexible, homogeneous with Node.sj, very high speed, good utility functions, and easy powerful queries.

Establishing relations between collections needs to be done manually and a bit error-prone.

Designing databases for websites and mobile application development.

It's very interesting for me when I was developing an application based on Node.js. In our application, everything was in JSON and was extremely easy and efficient to use MongoDB to store JSON objects.

I didn't like the errors that produced by MongoDB. They were not sometimes understandable.

A web-based graph-based search engine.

Native support of JSON is a great feature of MongoDB and a core requirement for my project. If you are new to MongoDB there are plenty of resources available to get you started with ease. One of the resources I'd recommend to anyone considering MongoDB is Mongo University. Their free courses give novice MongoDB users all the essential skills to start with MongoDB. More information is always available in MongoDB documentation.

Persnally I find that maintenance of MongoDB can be tricky and might require more training and hands-on experience. One must also be comfortable with command line tools. I am still learning about proper security settings on my project.

Flexibility and GeoSpatial queries and inexing. Full-stack development with Meteor.

The ease of use , simplicity, and blazing speed

It cannot be used for mission-critical application where data is very sensitive, as the mongodb developers recommend against doing that.

Store a huge set of user data. It has helped me scale up my business in ways that aren't possible with traditional DBMS

The speed of the engine, the scalability of it, sharding and the support of the various programming languages.

Installation is horrible. Too many machines roles in the setup. Map Reduce doesn't work as expected and is missing reliability (even from mongoDB team themselves)

Saving big data and querying it. Data that is coming in very fast from our applications, should be easily stored and fetched. Mongo solves this. Unlike couchbase, querying the data is easy and working nice.

MongoDB is great because its colelctions are in "json" and it makes it so natural to work with nodejs. I like the ease which you can protoype apps, you just have a bunch of data and throw it at mongo and then you can easily query it. Aggregations are very powerful and I always found the right solution for complex data.

There are other document databases which offer a way better integration for relations/joins. That's basically the first question that comes from a guy coming from mySQL which is difficult to explain to them how you would avoid them.

We had so much data around and using a database like mongo we made our data more flat, of course our DB size was very big but the performance improvements were visible. The benefit of it was that our pages were much faster to get delivered, data was all there and we did not have to go make 200 queries.

I've liked MongoDB from the beginning for it's ease of use. When building out a new app, it's no schema nature makes building the data layer a snap. It has very supported clients in pretty much every programming language, so I've never had an issue with Mongo support cross different environments.

Mongo doesn't have native support for joins, which can bite you later when your db grows and complex queries would be better served by using a join. With that said, blindly using Mongo for a highly relational project is a reason many people give Mongo bad reviews, but it was never supposed to be used for such scenarios. Although, I admittedly sometimes still use Mongo in highly relational apps because it's ease of use makes up for some of the relational query issues I may have. Also, mongo is password free by default, which unfortunately leads to a lot of users having public facing DBs with no password protection! Lastly, a production environment is pretty complicated to setup properly. For the most part, I'd recommend using a service to manage this for you. So in that regard, a production environment setup could be much easier to setup.

I love using Mongo in applications where the incoming data to be stored has no implicit structure. This is where a schemaless database shines.