My time using MongoDB has been excellent. MongoDB has become my go-to database choice because I work with data a lot. I have been able to handle a variety of rapidly changing data requirements with ease thanks to its flexibility and scalability. I like the document-based paradigm since it fits my data's dynamic nature nicely. I've been able to swiftly adapt and iterate thanks to the ability to store and query data in a schema-less manner. It has never been easier to obtain and analyze data effectively because to MongoDB's robust query language and indexing capabilities. My development process has been sped up by the easy connection with well-known programming languages and frameworks, allowing me to concentrate on creating strong and feature-rich applications. Along the road, any problems I met into were also greatly helped by the active community and thorough documentation. As a result, MongoDB has significantly changed the way I work with data by giving me access to a dependable, scalable, and adaptable database solution that meets all of my requirements.

MongoDB's unmatched flexibility and scalability are what I liked best about it. MongoDB has changed the game for me as someone who deals with continually evolving data formats and requirements. The document-based architecture enables me to store data in a manner that closely resembles the entities and connections seen in the real world, making it highly intuitive and simple to use. The dynamic schema gives me the flexibility I need to iterate quickly by allowing me to modify and develop my data model without being constrained. MongoDB's extraordinary capacity to scale has proven invaluable in helping me manage increasing data volumes and high-performance applications with ease. With MongoDB, I have the flexibility to scale horizontally with sharding or vertically with replica sets to match my changing demands. Additionally, data retrieval and analysis are now a snap because to the robust query language, numerous indexing options, and aggregation architecture.

If I had to pick one thing about MongoDB that I disliked the least, it would be the steep learning curve that comes with its sophisticated capabilities and intricate setups. MongoDB is a strong and feature-rich database that offers a variety of capabilities that may take some time and work to completely understand and efficiently use.

Using MongoDB for years, mostly as local storage in docker containers. Latest project is based on cloud solution.

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...

Built several multi-node clusters for data warehousing for ETL tools. Had a lot of issues early on to get it working. Documentation 2 years ago + was spotty but now its a lot better. Not to mention the software has evolved to include features sorely missing awhile back. We moved away from thsi product as it doesnt allow backups as robust as MSSQL and oracle but its great for certain types of data needs.

Can use a free version of it. And does allow clustering of it inclusive.

Compass client tool is useless versus other DB software tools. Pretty much all cli based access ot the collections within

With the large amount of built-in functions, I don't need to write some complicated queries in my project. I can also easily integrate with any of my projects. I won't need to extraneously install packages or tools needed to use the MongoDB Atlas. They also provide a custom role option for the CRUD option. This makes it more practical to use. Unlike other MySQL databases, MongoDB uses the BSON type to store data. that makes the database more fast and robust. And they also provide tools like MogoDB Compass for easier management. I can easily shift my data from one database to another using tools like Mongodump and Mongorestore. also one of the main reasons for me using MongoDB for its security. because they use popular platforms like AWS, Google Cloud, and Microsoft Azure to store data.

One of the fastest MySQL databases with a user-friendly database. You don't have to put that much stress into learning the MongoDB. The enormity of the built-in options makes this user easy to implement on their project. and easy to integrate with any framework (such as Node.js,Djanco, etc.). The detailed documentation with examples makes this even easier to use (in my opinion, most tools fail on complicated documentation with a lot of examples). The documentation provided by them was easy for even a beginner to understand. They also provide custom integration with top cloud-based platforms like AWS, Google Cloud, and Microsoft Azure. With the free storage space of 500 MP, everyone can use their database with a low amount of limitation.

From my point of view, I don't see any things I dislike about the MongoDB. They provided all the necessary things that I wanted.

MongoDB is for me the top database for microservices applications. It scales great and is easy to use. It has many integrations with popular programming languages. It is easy to configure it for heavy loads.

It is a NoSQL database by which it can be a certain entry threshold for beginners. Correctly selecting and setting up indexes can be a problem.

We used Mongo to host some incoming user data on one of our portals. We needed a solution that could host variable length data where the format could change semi-irregularly. Mongo was both quick to implement and reliable in use and has caused us no problems once we finished all the configurations.

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.

Very positive, allowed me to run a website with many many thousands of data entries, and all the usual features like relations and performance management that you would come to expect from a tool like MongoDB

Object oriented data storage is quickly becoming more popular and MongoDB makes it very easy to dip your toes into, and its blazing fast.

Adoption while fast, is still not there globally which means often resources on the web can be a bit scarce when compared to other database types.

It is very much fast and agile in nature.

It is very very much easy to use. It also manages multi server clusters. It has all the feature for documentations. I will definitely recommend everyone to use.

It is difficult to work with complex data.

Pretty decent and easy to use. Quality has improved.

Data storage, organization and maintenance.

Due to memory issues, I’ve seen duplicate data being created most times.

Useful for modelling social graph data and catalog data

Easy setup with various SDKs Good replication strategy Aggregation modelling is very straight forward

Collection indexing is very hard to update Increased memory usage

I needed a free but industry standard database for my Node.JS based library management application. MongoDB was just what I needed, I did consider MySQL but I wanted to try nosql / document orientated. It has been fantastic - it's hard to believe productions like these are free for all.

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.

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.

MongoDB has no proper structure like rows and columns in RDBMS. There is a feature called indexing where each and every row in the MongoDB database is identified with a unique id. The unique id is provided for each and every new document. The queries are easily understandable without involving any complex joins, unions. It also obeys the Atomicity, Consistency, Isolation, Durability known as ACID properties which are essential for a database. MongoDB supports sharding means huge data can be divided into smaller data and can be stored in multiple databases across a network. Different collections in MongoDB can be clubbed together and it also supports transactions which involve data needed from multiple documents across a collection. Based on these properties I have worked on different use cases and because of these features, work became simpler.

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.

Because the data storage is in JSON-like documents, it is very easy to understand and visualize. Used in class, and currently implementing an app for a physical therapist that tracks clients exercises and progress. I like the fact that the storage is encrypted.

I was introduced to MongoDB in a bootcamp. It is free and opensource. I wondered how good free could be. In my opinion it beat firebase. Objects can be defined graphically or via your code. It is easy to interface with Postman. Commercial upgrades are available. Currently using Mongo for an app. Supports Node.js. there is a lot of documentation available for beginners.

Not suitable for complex transactions. An occasional backup is recommended. After a crash, you need to check your logs. In fact, you may not know it crashed until you check your logs. With a crash or reset documents may fall into an "unconfirmed" category and are lost. This may have bee corrected in more current versions. I don't know.

It's straightforward to set up and offers multiple SDKs for use in application projects. The documentation is also readily updated and quickly followed.

Document size and nesting is limited in MongoDB, so if you have a requirement of document size more than 16MB or needing to have document with more than 100 levels, then this may not be a good choice.

MongoDB is a NoSql DB which helped us to store the non relational data. Searching and storing capacity of this tool is really good as compared to other databases

If you are moving on it from RDBMS than you may face some issues in the starting else it is really good to go.

MongoDB is at the core of our programme, which needs pace and accuracy. It's mainly used by the tech runtime team, with other teams using aspects of the software using it implicitly. For all online and mobile applications created for our customers, I use MongoDB as a database. It satisfies all of our requirements. The service is of high quality, being dependable, convenient, and durable. It's the most up-to-date and successful platform for software development.

Change streams and graph queries are two common database principles that MongoDB has quickly embraced. For popular programming languages, there is excellent library support. Developers will find it easy to set up and configure. It's also simple to write a query. Good scalability so data can be efficiently shared and is available quickly . There are a lot of tools and help online. Since there are so many ready-made options available, it's pretty simple to set up in some conditions. If you know JSON then it going to be easy for you to use.

The user interface is a bit difficult to understand at first. They could make it easier to integrate with other NoSQL databases. When opposed to a SQL-based database, extensive aggregation queries in MongoDB can be challenging.

Certain common operations are very very easy to spin up a one-off query for and utilize the data right then and there. In that sense, there is a very lightweight feel to developing with MongoDB at the start of most projects.

The design paradigms around MongoDB make it so that you will eventually want to add some sort of schema-type check somewhere in your stack. This will make development much simpler over time as the data begins to evolve. In general, there's a lot of other scaffolding you will want to do in order to sane-ly use a NoSQL as most people seem to want to (a quick start data store for a project that would otherwise benefit from a relational database). Not saying this is the "correct way" to use MongoDB, but just our experience within a system/framework like Meteor for example.

Count on NoSQL database technology, with a free but very useful technology, perfect for handling large amounts of data, making better use of the hardware resources of the applications that require it.

This type of non-relational database is a very useful tool today, where the amount of data handled in the web services are very abundant and a better way to store and take advantage of resources is needed, we use mongoDb, with its noSQL proposal takes better advantage of resources, since no paid licenses are needed, this money is used for hardware power, the expansion is easier since the database should not be restructured, it will keep the files linearly, that the escalation is horizontal and the load is distributed across all the nodes, taking better advantage of the hardware performance making any application more scalable.

It has its weaknesses, but you must know when to use this technology and when to use relational database, there are no transactions so if you need to use it, you should simulate them in a certain way, if it is very required in your application it is better to use sql, either Joins is available, so you should make several queries to interact between the data, you must be careful with this and know what technology is better with the application that will be developed.

I am utilizing MongoDB for deploying and storing document database which is one of the most significant categories of the NoSQL DB. Indeed, it encapsulates the data in BSON which is similar to JSON but with a BSON id. Moreover, MongoDB offers a very significant functionality, it supports the file storage. Unlike the relational database, it exempts the data from having a required schema. It provides libraries in numerous languages (i.e., java, python...) to connect with it.

I have not experienced any difficulties when working with MongoDB, however when building a sophisticated query with multiple joins it takes more times and it is normal as it is not a relational database.

MongoDB is a well-known choice for NoSQL Database and it can be used for free as well. Perfectly suited for a personal project or small project because we don't have to pay anything.

One thing that I feel annoyed about is the IP whitelist requirement in order to access the Database. Because my IP is dynamic it will be changing the address each time, I access the Database.

I'm using mongoDB for more than two years and It was great selection when I need to store documents which has unknown structure along with shared structures. That means, it's very easy to save a JSON in mongoDB. This is very helpful when creating embedded databases for java microservices projects using spring boot by adding dependencies via start.spring.io

MongoDB is a schema less database management system and it has a document based structure and can store collection values on documents. It is extremely faster than the relational database management systems and it is a light weight reliable application. And It is very easy to scale while the product is open sourced which is free of charge.

Database joins are not supported since this is a No-sql database.

Overall MongoDB is the good choice for NoSQL database. It is basically document type database. It suits well in Javascript environment of NodeJS, Angular, React etc. where we can directly store and read objects from the framework. It is one of the component of MEAN stack.

Most of the features we can get it for free. It is very light weight and easy database. It has support with almost all popular programming languages. its performance is continuously improving with the newer versions. It is very easy to setup and use.

Sometimes it goes difficult to create JOIN like queries with MongoDB. They have provided the aggregation framework but it does not give ease and like SQL Join queries. It can crash in the production environment.

Super easy to get started, perfect documentation, great developer user experience, great performances, easy query language.

Actually can't find anything I don't like about it.

Overall it is best as you can use the software with large database and unstructured data without any issues.It is schema- less database.

I am using mongodb with CRUD (create,read,update, delete) operation in my projects for doing modification with data and insertion.It is useful when you have instructed data and data size is very large,you can easily go with mongodb .It is very easy to install and setup if you are new to it.The query is very simple and easy to understand.

When you want to merge any two documents it is difficult as we can't used the join thing here.There is one default transaction support which we need to handle ourself.