MongoDB

What is MongoDB? Introduction, Architecture, Features & Purpose

MongoDB is becoming more and more popular as a document-oriented data store. Perhaps you initially heard about this during a DevOps meetup presentation? You might also be searching for an introduction to MongoDB or how to begin using it.

MongoDB is a free, open-source database that provides high availability, security, and fault tolerance. In case you have no idea about what MongoDB is, then here is a little introduction in order for you to understand better.

What is meant by MongoDB?

Companies like User Testing, Expedia, and Gawker Media use MongoDB, an open-source document database. It has the benefits of both relational and non-relational databases, with its own query language (a subset of JavaScript).

It provides high availability with a fault-tolerant architecture. This document-based database offers high performance along with an easy-to-install feature and easy scalability. MongoDB also supports indexing during the query operation with very sharp performance for searching as (JSON) a data format. MongoDB can be installed on Mac OS, Linux, and Windows Operating Systems.

MongoDB is a free, scalable, and highly compatible NoSQL database that is improving the speed of operations and reducing storage costs for enterprise apps. Imagine having all the data in one place, in a flexible way that lets you tailor your queries to match your needs. MongoDB gives you a much better interface to work with data – including rich query languages like Hive, which allows you to attach data structures to URLs and store them in a database alongside other documents. To check MongoDB Pricing Click Here.

History of MongoDB

MongoDB is now considered as a PAAS in 2007, which is Platform as a Service. In 2009, the first version of MongoDB was released, in the form of a C++ library. Over the next two years, the product evolved from a development kit to a standalone database server. By late 2010, MongoDB had become a key-value pair storage system and subsequently added support for arrays and documents.

The first ready-made version of MongoDB is considered to be version 1.4, which was released in March 2010. MongoDB 2.4.9 was a very modern and well-built version that was released on January 10, 2014.

Purpose of MongoDB

In the beginning, MongoDB was built to solve a specific problem for one company. Since then, it has become clear that there are several interesting problems in the database development space, and we think there are several interesting solutions for these problems. While our initial purpose was to provide a solution to a specific problem, over time we have broadened the scope of what we offer to include high-impact solutions for general database and NoSQL problem-solving.

  • MongoDB provides a free and open-source, document-oriented data store.
  • MongoDB offers high availability, elastic scalability, and high throughput.
  • MongoDB’s clustering and automatic failover enable high availability.
  • MongoDB offers elastic scalability by auto-sharding data across many servers.
  • MongoDB has a high throughput because it can handle thousands of simultaneous operations per second.

The main purpose of creating MongoDB:

  • Scalability
  • Representation
  • High accessibility
  • Scale from single server setups to large and complex multi-site architectures.
  • MongoDB Essentials
  • Develop faster.
  • Easier to use.

Key Features of MongoDB

  1. Indexing- In MongoDB, we can create any index we want to save more performance.
  2. Replication – In MongoDB data is stored in several replica set servers so that it could be back easily if there is any failure at the replica server.
  3. Support ad hoc queries– Support complex queries from the start.
  4. Duplicating Data-MongoDB is an excellent system for dealing with this problem because it allows you to use multiple replicas of data in a single database. This means multiple users can access data at the same time without risking data loss while keeping the main database available in case one of the users quits or crashes.
  5. load-balancing – It automatically configures load balancing due to the data provided by the segment.
  6. Support map reduction and aggregation tools.
  7. Use JavaScript instead of procedures.
  8. The schedule database is written in C++.
  9. Provides high performance.

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