Why NoSQL good for Big data?
Big Data describes a large and complex data sets, which is usually referred to massive, rapidly expanding, varied and often unstructured sets of digitized data that are difficult to maintain using traditional software tools. That’s why we need a powerful and a specialised tool like NoSQL.
NoSQL is a whole new way of thinking about a database. NoSQL is designed especially for storing Big Data. This is a new type of database which is becoming more and more popular among web companies today. Because, the website with a large number of customers need to respond quickly to deal a successful marketing campaign with hundreds of or millions of users, but it’s getting slow down. This situation can be handled by NoSQL more easily and efficiently. NoSQL has provided simplicity, scalability and improved performance with traditional relational databases.
Let’s dive into deep to find out - Why NoSQL is better for Big data?
Nature of Data
The data is stored in the form of flat collections in NoSQL Databases such as Couchbase, Cassandra, and MongoDB, where this data is duplicated repeatedly and a single piece of data is hardly ever partitioned off, but everything stored in the form of an entity. This kind of single entity make reading or writing operations more easier and faster, also store and process data in real time.
The most beneficial aspect of NoSQL databases is the ease of scalability to handle huge volumes of data. If you operate an eCommerce website, you will have tons of customers who visit your website. If you are using a relational database the you'll have to meticulously replicate and repartition the database to fulfill the increasing demand of the customers. Increase in demand, the relational databases tend to scale up vertically that means they add extra horsepower to the system to enable faster operations on the same dataset.
But, NoSQL Databases are scale horizontally which added a extra nodes with commodity database servers to the resource pool, so that the load can be distributed easily.
Relational databases using SQL which is the database landscape for maintaining integrity through the ACID properties (Atomicity, Consistency, Isolated, and Durable) of transactions. With this system, changes are permanent, leaving the data in a consistent state which occur difficulties.
NoSQL Databases work on the concept of the CAP priorities (Consistency-Availability-Partition Tolerance). This system can change anytime devoid of executing any query because node updates take place every now and then to fulfill the ever changing requirements and will become consistent in the long run.
When using document-oriented NoSQL Engine, a user can store any type of data (flexible schema/schema-less) allowing you to archive anything.
As companies strive to adopt Big Data sooner than rivals, the competitive advantage of Big Data deployment is increasingly coming from technologies that are still on the fringes of the domain proper. NoSQL has matured into one such tech and has become a must-have skill for any professional hoping to break into the lucrative Data Science industry.
For large sets of data distribution
The NoSQL database is an approach to managing data and database design to dealing with large sets of distributed data. It consists of a wide range of architectures and technologies that seek to solve performance and scalability issues with Big Data. It is used primarily when enterprises need to analyze and access huge amounts of unstructured data or data that is stored on multiple virtual servers over the cloud. NoSQL databases follow the BASE (Basically Available, Soft state, Eventual consistency) approach instead of ACID.
Performance and productivity
NoSQL database improves the programmer’s productivity with the use of a database that matches an application’s needs. It also enhances the data performance with the use of some combination of handling larger data volumes, the reduction of latency, and the improvement of throughput.
Offers better technologies
NoSQL encompasses a wide array of different database technologies. Today’s NoSQL database solutions offer a number of advantages over RDBMS products, such as high performance, scalability, and availability. Organizations looking to store and analyze massive amounts of structured, semi-structured, and unstructured data files and sets, especially in real time that will be better served by a NoSQL database. NoSQL databases also offer an efficient architecture that scales-out horizontally. This means that increasing storage and compute capacity is merely a matter of adding more commodity servers or cloud instances.
To remain competitive in today’s experience-focused digital economy, enterprises must innovate. They have to do it faster than ever before. And because this innovation centers on the development of modern web, mobile, and IoT applications, developers have to deliver applications and services faster than ever before. Speed and agility are both critical because the applications evolve far more rapidly than legacy applications like ERP. Relational databases are a major roadblock. They don’t support agile development very well due to their fixed data model. NoSQL document database fully supports agile development, because it is schema-less and does not statically define how the data must be modeled.
Using flexible data schema NoSQL Databases can help develop and deploy many online advertisements as ads need a wide number of audience. NoSQL can build such an application that can be used to manipulate such data.
One can archive data using NoSQL databases. NoSQL databases can store huge amount of data and they can store any kind of data (structured/unstructured). So, if you want to archive any kind of data you can use NoSQL databases.
Social applications can scale from zero to millions of users in the duration of a week. The database needs to be able to manage the unstructured inflow of data and should scale horizontally.
The NoSQL Database is a good reference for someone looking for more information. Some NoSQL systems provide native MapReduce functionality that allows for analytics to be performed on operational data in place. NoSQL is better for businesses whose data workloads are more geared toward the rapid processing and analyzing of vast amounts of varied and unstructured data, aka Big Data.