MongoDB Reviews

We developed a social network and as a first approach we had everything based on a relationship DB but the loading times of the data feed were really slow. We have migrated everything to MongoDB and the feed loading times have drastically reduced.

No problems encountered during use, but if you don't structure your data correctly but maintenance becomes very complicated.

Ease of use.
Customer support and documentation.
Speed and functionalities.
Flexibility.

May be hard to maintain if the structure is created in the wrong way.
Beginners may get lost in more complicated queries

-Easy Setup
-Getting simple data in/out is painless & straightforward
-Basic analytics are easy, as is managing multi-server clusters

-Working with complex data is a difficult.
-Many original features or design choices were incorrect and slow to be corrected. For example, timezone support is minimal and days/dates/months use a custom numbering rather than ISO. Mongo is only now adding ISO versions of aggregation commands

The ease of use. JSON type document helps me to scale my database model as the application is growing. Along with the powerful query language of MongoDB it's so easy to pull data from the data.

MongoDB also gives free 500MB is space without giving any credit card and I found that very awesome!

I would like to see the compass getting more powerful and having many more features.

MongoDB was our go-to solution for a NoSQL database due to the ease of installation and simplicity. We had used Mongo before for smaller projects but decided to use the MongoDB Atlas service to have a reliable instance online. Using the hosted version alleviated a lot of the configuration issues we had experienced also, although it isn't required to use the hosted version depending on the use case.

The visualization aspect of Mongo constantly was an issue for our team. We wanted to display dashboards of our data through a variety of methods but most were difficult to implement using Mongo, or were simple/slow at best. There was also a lot of trouble trying to connect MongoDB Atlas with our AWS VPC, specifically so that our cloud functions could access it.

Virtualization is perfect feature for MongoDB to understand your dataset and performings.

MongoDb is quite expensive when you compare other kind of database platforms.

Ease of connecting to nosql databases with URI as well as entering credentials separately. We can save the connections in the MongoDB and later on connect those with a single click.
It is quite fast as we get result in no time. Also it is quite easy to use. Also while writing queries, we can apply different filters and get the filtered data.

switching between different database is tough, as we need to close old one and connect new one.
opening collection again and again is also a issue, as there is no tab options.

I have been using the software for my daily work and there not even a day i go without having blown away by the software. Who would have thought that
working with big data is that easy.

The same interface is sometimes a little boring though there is not much smthing to say abou the performance, but i feel the interface is sometimes really monotonous and boring to work with.

The interface of the application is simple and user-friendly. The application is easy to use. You can perform all your operations regarding the database.

There is nothing wrong with the app. It's nice to have the visualization feature added.

I used this while studying and I majorly used it for storing big data

Only thing I liked least was that it used a lot of memory

I love how MongoDB integrates with code in such a way that queries look just like any other code. I also love how the documents from MongoDB are returned natively to Node.JS as objects without any mapping at all. MongoDB is an intuitive and very performant database, I recommend trying it if you haven't.

The big thing with MongoDB you have to get your head around is the whole redundant data thing - it is usually recommended that you store a lot of redundant data in your documents instead of having data normalised with relationships as you would in a relational DB. Have redundant data can make your query code really simple, but it can make your update code very complex / cumbersome. However, you can opt out of this approach and use MongoDB with relationships - I would recommend using Mongoose (an npm package) that will handle a lot of the work with relationships for you.

MongoDB has integrations with almost all computer languages used today, with even having an integration with Erlang (a very rarely used language). The drivers are easily available from open source contributors and works amazingly well. For a No-SQL database, it is amazingly well managed and easier to use in almost all other languages.

Its sort of confusing to manage the access control levels of the users, as it is all stored in json file. If there was a way to sort of make this process graphical or interactive, it would have reduced many access threats in a database.

I like the Atlas Cloud solution. It enables various tricks and cross-integrations of single database between multiple apps (containers) with simple user management - for a reasonable price.

I cannot get over this Atlas Compass UX issue - I want to open at least two "tabs" with collections at the same time. This is not possible and even worse, when you switch between collections, thee state is completely reset.

So I'm compiling the search query carefully with all the commas, brackets and identifiers, I often need to search for ID from another collection or maybe from the same collection. When i change collection scope -> BAM! The whole query is gone :( The input should retain its actual value...

Second "issue": When it comes to schema changes in living DB, sometimes it behaves unexpectedly (no error, no data). Maybe I'm doing something wrong, but I would like to know it...

I don't usually rave about products, but I do about MongoDB.
* MongoDB's schemaless document-centric approach to database makes it easy to store any kind of data I need to, even subdocuments and array fields with minimal fuss within code or tools. This allows for a lot of flexibility and makes it easy to upgrade or refactor existing software.
* MongoDB's indexes provide amazing performance even in a schemaless world. Simple and compound indexes, as found in the relational database world, are just the start. Add to that multikey indexes (indexes over array fields), string and geolocation indexes, and indexes where entries expire documents with time. Mongo has it all.
* MongoDB's approach to scalability - using replica sets for high availability and fault-tolerant failover and sharding databases over a potentially large number of servers - makes it easy to scale huge amounts of data without overly expensive hardware and failover complexity.
* MongoDB driver support is available for a variety of languages.
* Mongo University, free graded courses covering various aspects of MongoDB from development to administrative activities to security, etc., offers a solid path to learning.

I'm a huge proponent of MongoDB but because of the nature of schemaless document-oriented databases, there are still some problems for which a relational database is still the answer. There are some applications and technical domains where relational databases still have a huge lead over Mongo for performance.

One of the most difficult parts of software development, especially with complex projects, is keeping the software maintained. As business requirement change, the effort required to make those changes grows over time. MongoDB opened up a whole new world for me. I can make structural changes to my underlying data with ease without too much modification the data access layer. It reduces initial development significantly, and allows my team to pivot to new requirements with unprecedented ease. Because related data is encapsulated, queries are much faster, and our software is extremely performant. Highly recommended.

The tooling isn't great. Compass is a decent tool for accessing and lookup, but it lacks polish. It's slow to start up and sometimes difficult to pull up the data I'm seeking

MongoDB integrates very well with JS-based server code. It's fast and its dynamic, NoSQL nature allows for a lot of flexibility and creative use.

As MongoDB isn't as ubiquitous as other solutions like MySQL, there's a bit less tooling available and some IaaS platforms treat it as a second class citizen.

Mongodb is a no-sql( not only sql) database.so it is different from other traditional database.its support partitions and indexing both so the data fetching is way more faster then other traditional database. We can use both partition and indexing for storing data and also make use of partition we can fetch data in less time as compared to others database and its store data in horizontal way so no relation and no scheme needed so its gives faster performance in data analysis.

Mongodb doesn’t support procedure which is now supported bat many other no sql database and mongodb have little bit complex queries to understand for a new user.

MongoDB is incredibly easy to set up and use. The fact that non-relational DBs are better for more unstructured data, makes it so that you don't necessarily have to know exactly what the end state is going to be before building your schema. Its data throughput is also a key differentiator, so anything with Big Data is going to be a good fit for a non-relational DB and MongoDB, in particular. Finally, the team behind MongoDB is constantly improving the product and releasing updates, and there are several good data viewers in the market, including one from Mongo, for viewing the data and creating queries.

Creating metrics dashboards can be challenging due to the potential need for JOIN queries in your data. Anything that contains these will be harder to aggregate. Their aggregation framework can be hard to use and limiting for certain requirements.

1) There is no fixed schema like RDBMS. We can alter the table structure insert any number of rows and columns.
2) Data retrieving from this No-SQL database is very much fast when compared to other No-SQL databases.
3) Very easy to install. Provides JSON data support.
4) Can be integrated into different languages like Java, PHP.
5) There are no complex joins of queries like RDBMS.
6) The technical support can be available from MongoDB clients in case of any complex issues that occur while working.
7) Having extra features like a backup of stored data, sharing the data to multiple systems across the network is an added advantage.
8) Handles unstructured data i.e the data which has no format, no proper structure.

I did not find any flaws with this software.

We can see that MongoDB are on a growth-mindset, constantly adding new features like serverless functions, analytical text search, global write ops, and many other at-scale, enterprise level features. Some of these are already helping us reduce our infrastructure costs, for example, we've recently began switching off our third-party search service that was costing us £££ thanks to the introduction of MongoDB search.

We've had some recent headaches around the MongoDB connection string changes and issues with whitelisting some of our private VPNs on AWS. But these are minor issues. I personally think the Performance Advisor feature is poor - it would be far better to get a list of all unindexed queries listed by overall usage by time-period, rather than the adhoc suggestions that we see.

Very fast installation and use. It has very complete tools to manage you, such as the Mongo Compass or the possibility of having everything in your cloud with Mongo Atlas. The installation is very simple and the power of the tool is incredible and integrates perfectly with our system built in NodeJS. It has a very detailed documentation which facilitates its integration.

The main cons is that it does not have the possibility of making queries with JOINS but this is a limitation of NO-SQL databases

Mongo DB is non relational database (NoSQL). It is a document database. it has good query capacity. Very easy to install and setup Mongo DB. Also Mongo DB is schema-free, there fore our software (code) defines the schema. It support BSON data format, there fore no complex to write code with mongo db (most of programming languages support BSON data format. We can index the mongo collections and increase the query performance

When we need to query using two mongo collections (join two collection), we can use lookup feature. but the problem is Mongo DB lookup feature is slow. Also we have no option to run query among two or three collections like as Elastic Search. When we using Elastic Search we can run query among two or three indexes(collections). There for in Elastic Search we can move historical data to separate collections and improve query performance. if we need query with historical, Elastic Search support it. But using Mongo DB we have to handle it in programming side.

First thing is there's no need of any Queries; it is the king of NoSQL. MongoDB is easy to user and learn too and also a flexible schema for changing data elements. Being a web developer, i work on JavaScript, so it's too good for Integrating with JavaScript backend like NodeJS. For the beginner and new comers, they have Mongo DB for free with certain amount of data storage.

Unlike SQL, it has no joins, which can sometime be an issue in some data retrieval cases. Sometimes it works very slow in the cloud environment. There are no functions available for Transaction. MongoDB's documentation is much confusing to the users. Even if it's easy to use and learn, learning MongoDB might take some time. I thinkg it is hard to work with complex queries.

Really speedy and requires less memory.
We can create collections without a definite number of rows and columns to come.
We can add data without restrictions
It gives a JSON output which is really easy to work with
Easy to add , edit and remove data
If a certain section has more than one data, we can insert them as sub arrays, and it makes the developments so flexible.

The free version allows limited memory so that we have to upgrade it to insert unlimited data. Other than that this is the best.

MongoDB's support for setup and when we have run into problems was the best part about using Mongo and why I've come back to it many times.

MongoDB has good relationships with other providers but the fact that it's not part of a larger suite of cloud-based solutions is a shame.