NoSQL Databases Overview

The world of data is constantly changing and evolving every second. This in turn has created a completely new dimension of growth and challenges for companies around the globe. By accurately recording data, storing, updating and tracking them on an efficient and regular basis, companies can address their challenges on one hand and make use of the immense potentials offered by this sector on the other hand.

A database management system stores, organizes and manages a large amount of information within a single software application. The use of this system increases efficiency of business operations and reduces overall costs.

In another words…

A database is a collection of data stored in an orderly manner. To run a system efficiently, you’d need an effective memory of the past and present records that went into and/or came out of that particular system. The same applies to a business or organization that would require the cooperative efforts of a number of individuals. For this purpose, companies, large and small, and organizations like hospitals, schools, and universities utilize a very useful method of acquiring, assembling, and sharing the data in systematic ‘Entities’ that are stored within different types of databases.

What Are Databases Used For?

  • Allows a business to make more informed business decisions.
  • Efficiently store and retrieve related information.
  • Helps analyze and aggravate business data.
  • Collect and store crucial customer data from different applications.
  • Delivers data-driven timely, personalized applications, and real-time analytics.
  • Ensures accurate, reliable, and immediate access to crucial business data that can be used by different business departments to comprehend data patterns, generate reports, predict future trends.
  • Often data Is mapped through hierarchical databases used by legacy systems to relational databases used in the data warehouses.
Source: Toptal

Types of Databases Explained:

But we’ll talk specifically about NoSQL in this particular blog.

Non-Relational Databases

A document can have a name, address, and product in a collection; at the same time, another document can have just a name and product in the same collection as there are no particular schema to these documents. Also, different collections might not necessarily have relations among them.

The different types of non-relational databases are:

Key-Value Stores

Wide Column Stores

Document Stores

Search Engines

Graph Databases

Why should you use a NoSQL database?

  • Flexibility: NoSQL databases generally provide flexible schemas that enable faster and more iterative development. The flexible data model makes NoSQL databases ideal for semi-structured and unstructured data.
  • Scalability: NoSQL databases are generally designed to scale out by using distributed clusters of hardware instead of scaling up by adding expensive and robust servers. Some cloud providers handle these operations behind-the-scenes as a fully managed service.
  • High-performance: NoSQL database are optimized for specific data models and access patterns that enable higher performance than trying to accomplish similar functionality with relational databases.
  • Highly functional: NoSQL databases provide highly functional APIs and data types that are purpose built for each of their respective data models.

Among all NoSQL databases MongoDB is one of the most popular NoSQL databases out there today and the question is why it is so? Lets explore MongoDB each part in depth

What is MongoDB?

Being a NoSQL tool means that it does not use the usual rows and columns that you so much associate with the relational database management. It is an architecture that is built on collections and documents. The basic unit of data in this database consists of a set of key–value pairs.It allows documents to have different fields and structures. This database uses a document storage format called BSON which is a binary style of JSON documents.The data model that MongoDB follows is a highly elastic one that lets you combine and store data of multivariate types without having to compromise on the powerful indexing options, data access, and validation rules. There is no downtime when you want to dynamically modify the schemas. What it means that you can concentrate more on making your data work harder rather than spending more time on preparing the data for the database.

Architecture of MongoDB NoSQL Database

Database: In simple words, it can be called the physical container for data. Each of the databases has its own set of files on the file system with multiple databases existing on a single MongoDB server.

Collection: A group of database documents can be called a collection. The RDBMS equivalent to a collection is a table. The entire collection exists within a single database. There are no schemas when it comes to collections. Inside the collection, various documents can have varied fields, but mostly the documents within a collection are meant for the same purpose or for serving the same end goal.

Document: A set of key–value pairs can be designated as a document. Documents are associated with dynamic schemas. The benefit of having dynamic schemas is that a document in a single collection does not have to possess the same structure or fields. Also, the common fields in a collection’s document can have varied types of data.

What makes it different from RDBMS?

Go through the following table to understand how exactly an expert NoSQL database like MongoDB differs from RDBMS. This blog has elucidated nine different comparisons between the two.

Important Features of MongoDB

  • Index Support: Any field in the document can be indexed.
  • Replication: It supports Master-Slave replication. MongoDB uses the native application to maintain multiple copies of data. Preventing database downtime is one of the replica set’s features as it has self-healing shard.
  • Multiple Servers: The database can run over multiple servers. Data is duplicated to foolproof the system in the case of hardware failure.
  • Auto-sharding: This process distributes data across multiple physical partitions called shards. Due to sharding, MongoDB has an automatic load balancing feature.
  • MapReduce: It supports MapReduce and flexible aggregation tools.
  • Failure Handling: In MongoDB, it’s easy to cope with cases of failures. Huge numbers of replicas give out increased protection and data availability against database downtimes like rack failures, multiple machine failures, and data center failures, or even network partitions.
  • GridFS: Without complicating your stack, any sizes of files can be stored. GridFS feature divides files into smaller parts and stores them as separate documents.
  • Schema-less Database: It is a schema-less database written in C++.
  • Document-oriented Storage: It uses BSON format which is a JSON-like format.
  • Procedures: MongoDB JavaScript works well as the database uses the language instead of procedures.

Why do you need MongoDB technology?

  • No downtime while the application is being scaled
  • Performs in-memory processing
  • Text search
  • Graph processing
  • Global replication
  • Economical

Moreover, businesses are increasingly finding out that MongoDB is ticking all the right boxes when it comes to meeting the business requirements. Here is how:

  • MongoDB provides the right mix of technology and data for competitive advantage.
  • It is most suited for mission-critical applications since it considerably reduces risks.
  • It increasingly accelerated the time to value (TTV) and lowered the total cost of ownership.
  • It builds applications that are just not possible with traditional relational databases.

Listed below are the six aspects through which you can realize the benefits of MongoDB:

Fast and Iterative Development: Changing business requirements will no longer affect successful project delivery in your enterprise. A flexible data model with dynamic schema, and with powerful GUI and command line tools, makes it fast for developers to build and evolve applications. Automated provisioning enables continuous integration and delivery for productive operations. Static relational schemas and complex operations of RDBMS are now something from the past.

Flexible Data Model: MongoDB stores data in flexible JSON-like documents, which makes data persistence and combining easy. The objects in your application code is mapped to the document model, due to which working with data becomes easy. Needless to say that schema governance controls, data access, complex aggregations, and rich indexing functionality are not compromised in any way. Without downtime, one can modify the schema dynamically. Due to this flexibility, a developer needs to worry less about data manipulation.

Reduced TCO (Total Cost of Ownership): Application developers can do their job way better when MongoDB is used. The operations team also can perform their job well, thanks to the Atlas Cloud service. Costs are significantly lowered as MongoDB runs on commodity hardware. The technology gives out on-demand, pay-as-you-go pricing with annual subscriptions, along with 24/7 global support.

Integrated Feature Set: One can get a variety of real-time applications because of analytics and data visualization, event-driven streaming data pipelines, text and geospatial search, graph processing, in-memory performance, and global replication reliably and securely. For RDBMS to accomplish this, there requires additional complex technologies, along with separate integration requirements.

Long-term Commitment: You would be staggered to know about the development of this technology. It has garnered over 30 million downloads, 4,900 customers, and over 1,000 partners. If you include this technology in your firm, then you can be sure that your investment is in the right place.

Thank you for your valuable time, keep learning!

Passionate about ML