Utilized for storage of high volume data, MongoDB is an open-source, NoSQL document database. Founded in 2007, currently, the database enjoys a huge community of developers and supporters.
Because of its favourable and flexible features aligning to the business needs, it has become very popular. Businesses can opt for a document-oriented data model or/and an unstructured query language as it offers both.
Based on a scale-out architecture, the database enables professionals to create applications with the help of various agile methods. In short, Mongo DB is helping businesses of different sizes to achieve their development goals.
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Packed with many benefits, Mongo DB offers great perks to the users.
To start with, developers do not need to restrict themselves to predefined schemas as Mongo DB does not have one. That said, its dynamic schematic architecture suits the non-structured data and storage.
This fits best for businesses that are constantly evolving and hence their data. With a flexible database model such as that offered by Mongo DB, it becomes simpler to adapt to the changes.
To maintain a large pool of data, MongoDB makes use of Sharding – a process that divides and distributes the data from a bigger database set to multiple servers.
This feature is crucial in cases where one server is not able to handle a large database size.
Known for its simplicity, MongoDB has an easy to learn query syntax which is even simpler than the SQL syntax. The query language is expressive enough and helps developers to work with this database without any hassle.
Keeping aside the advantages, there are certain limitations that Mongo DB exhibits too.
MongoDB is popular for maintaining high-speed performance. However, this majorly depends on the indexing process.
If not performed right, incorrect indexing can lead to extreme discrepancies. And, it will also lower the performance of the database exponentially.
Duplication of data is another reason why professionals find it difficult to work with Mongo DB. With a lack of properly defined relations, it sometimes becomes a challenge in handling data sets.
MongoDB often ends up demanding a high amount of storage. This is basically a consequence of the lack of joins functionalities. Eventually leading to a higher probability of data duplication.
All these problems further add up to data redundancy, ultimately requiring unnecessary memory space.