An Introduction to MongoDB and Its Relevance in Database Administration

April 1, 2019

Data is witnessing a huge rise across the globe, so as the need for data management for enterprises. We can see increasing interest and evidently observable trend around the latest wave in non-relational DB, which is also called as “NoSQL” database management. Businesses are now seeking innovative methods to effectively manage the data flooding and also cost-effective mode of storage and processing data. This paved way to the introduction of many alternate DBMS tools, which are totally different from the relational traditional database management approaches. This is where MongoDB comes into the picture.


By definition, MongoDB is a new open-source solution for database administration, which uses an innovative document-centric database model. MongoDB is a non-structured query language, which is now considered to be the most powerful among the NoSQL databases there around nowadays. NoSQL means MongoDB doesn’t function in the manner of database tables with rows and columns, which we are used to. It is a different architecture which is built on documents and collections.

The basic unit in the NoSQL database is a unit of data which consists of a unique set of key-value pair. This allows the documents to contain different structures and fields. MongoDB uses a specific storage format known as BSON, a binary system of the JSON documents.

Data model followed by MongoDB is possessed more elasticity, which allows to combine various sets of data and store multivariate types without compromising on indexing options, validation rules, and data access. This means there will not be any downtime when you are trying to modify the data schemes.

MongoDB architecture

  • Database – In simpler terms, MongoDB can be compared to a container of data. Each database inside it has its own unique set of files on the comprehensive file system with multiple DBs on every MongoDB server.
  • Collection – It is a group of documents. In conventional RDBMS, the collection is equivalent to a table. Collection, as a whole, exists in a database. Inside collections, you can find various documents with varied fields; however, all documents within a specific collection are of the same purpose.
  • Document – Document is a combination of the key-value pairs (the primary unit of data). Documents in MongoDB are tied to the dynamic schemas. The advantage of a dynamic schema is that each document in a collection doesn’t have the same fields or structure. The common fields in the collection’s document also have different data types
  • Queries – both document-based queries and ad-hoc queries are supported.
  • Index support – Unlike conventional DBMS, we can index any field in the given document.
  • Replication – MongoDB supports master-slave replication.
  • Multiple servers – Databases can run simultaneously on multiple servers. Data can also be duplicated in case of any hardware crash.
  • Auto-Sharding –Distribution of data across various partitions known as shards. This facilitates an automatic load balancing.
  • Failure handling – As said above, there is a large number of replicas, which ensures enhanced protection against rack failures, machine failure, or even data center failures.

MongoDB vs. RDBMS

Non-relational DB Relational DB
Document-oriented Row-oriented
Field-oriented Column-oriented
Key-value pair collection oriented Table-oriented
Uses JavaScript for querying Not using JavaScript for querying
Easy setup Expert set up requirements
Unaffected by add-on SQL injection Vulnerable to new SQL injection
Hierarchical storage structure Non-hierarchical storage
Possesses dynamic schema Possesses predefined schema


Why we need MongoDB?

As suggested by, MongoDB has already overcome many of the pitfalls in existing database systems, the major one among these being scalability. As every business system need to upgrade their database systems more frequently now, scalability is a necessity. MongoDB possess exceptional capacities in terms of scalability, which makes it easy for users to fetch data and facilitate automatic integration. Some other reasons why need MongoDB include:

  • There is no downtime while this application is scaled
  • Text search enabled.
  • Allowing graph processing
  • MongoDB is more economical
  • It possesses the right mix of technology upon data to offer a competitive advantage.
  • Best suited for critical applications with significantly reduced risks.
  • Accelerates time-to-value and reduced total cost of ownership.
  • MongoDB can be now used to build applications which are not possible with the traditional databases.

Along with these, most of the businesses try out MongoDB identified that it is meeting almost all existing requirement when it comes to effective business database management of modern times.

Features of MongoDB

  • Flexible model

Unlike the SQL databases, MongoDB can store data in more flexible JSON-type documents, which will help to make the data more persistent and combining data much easier. The object in an application is mapped to the document model, with which it becomes much easier to work with data. The specific schema enables better governance of controls, complex aggregations, data access, and indexing functionality. Using MongoDB, one can modify the schema without any downtime. Enjoying this flexibility, developers need not to worry about the data manipulation.

  • Reduced cost of ownership

Along with developers, operation teams may also perform their job in a better way on MongoDB with cloud service support. The cost of managing MongoDB is largely reduced on its commodity hardware. This enables more pay-as-you-go and on-demand pricing in a subscription model and round-the-clock support.

  • Integrated Features

One may get a fair set of real-time applications and analytics tools for better management of data. This includes data visualization, geospatial search, text-based search, event-driven data streaming, in-memory performance graph processing, global replication, etc. to be done securely. In the case of conventional RDBMS, accomplishing these require a lot of complex administration along with on-going integration requirements.

While thinking of database migration; however, one needs to remember that MongoDB will not support the SQL language. The querying style of MongoDB is more dynamic based on documents, so it remains a document-based query language which. On the other hand, MongoDB is much easier to scale up, and there is also a need to convert applications objects to the database objects for proper mapping. It also deploys an internal memory to provide faster access to the data.

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