MongoDB Erfahrungen

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.

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.

It is Universal and is compatible with many different applications.

Not sure of what kind of storage space that it will require or consume.

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.

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

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.

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.

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.

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.

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.

The speeds at which the aggregation queries are churned by the database cluster running on 8 GB virtual nodes.

The enterprise versions are pricey. The license cost is dependent on cluster sizes and data ingress costs are additional if the cluster spans a data center.