Trends in Database Management Systems

An IBM Marketing Cloud study suggests that 90% of the data on the internet has been created since 2016. However, by 2025, it is estimated that 463 exabytes of data will be created daily, globally.

Our dependency on digital means is growing with websites, social media presence, and a visible growth in the electronic payments systems. Businesses are migrating towards a fast-paced environment by implementing futuristic technologies that safely structure and manage their data. After all, this valuable resource enforces an informed decision-making cycle that supplements a competitive edge. Users, too, are evolving with easy access to innovative technologies, seeking real-time access to support their decision-making process. 

Even though it seems that data is wonderfully transforming our lives (such as WWW), creating and managing it online is critical. Data assists businesses in finding relevant relationships that are vital to an organization’s growth. It can be anything from a sales inventory, an employee list, or something that needs tracking. It is extensive and exhaustive. Therefore, your regular pen drive or hard disk can not store it. It must be stored perpetually on a server in a readily available format. It has to be leveraged and assessed seamlessly but should also be safe from a breach, piracy, and tampering. 

DBMS is a software application used to conveniently access, create, retrieve, and update data from various databases. It is like an interface between the database and its end users. It maintains optimal performance, efficiency, privacy, and security while tackling challenges hampering the fluidity of businesses. DBMS is an integral part of back-end development.

When you are banking online, keeping an account of your monthly payments, or managing travel reservations, notice carefully the real-time updates happening on the page. It is the work of DBMS, giving commands to the system upon request to load, retrieve, or modify the existing data. Without you having to reload or refresh the page, the system is continually updating everything for you to see in real-time. 

DBMS can be easily integrated into programming languages such as Java and Python, to enable connection with any application or website that is accessible to multiple users.

As of March 2020, there are more than 300 types of DBMS software in the market and the numbers make sense when we look at the zettabytes and yottabytes of data being churned. Choosing the right DBMS software to meet your business requirement is not only vital but overwhelming. Data storage requirements tend to vary from company to company, with core specifications centered around the cost, capacity, scalability, accessibility for immediate consumption, and useability for future reference.

Since the inception of DBMS, the world has seen and used various kinds of databases. In the past few years, SQL, NoSQL, and NewSQL have remained most relevant and used, and are expected to remain so in the foreseeable future.

Relationship Database (formatted and structured data) is accessed and managed using only one language called SQL- Structured Query Language. It is used by corporate behemoths such as Accenture, Microsoft and IBM, etc.

Two other database concepts that have, of late, been integral to modern applications such as mobile, web, and gaming are NoSQL and NewSQL. 

NoSQL comprises all those databases that are non-relational like hierarchy, network, and object-oriented databases. It interacts with several different forms of stored data that can be structured, semi-structured, or even unstructured. 

It is used by the likes of NetFlix, LinkedIn, and Twitter.

NewSQL is a hybrid approach to managing humongous data. You need the best of both SQL and NoSQL to build a perfect solution. Companies dealing with Big Data and IoT often tend to use this new database.

Database Developer-

A DB developer is tasked with analyzing and refining data that foster organizational growth. These developers work with generic and proprietary APIs to build applications that interact with a DBMS and maintain the quality of the data and information. With skilled training in key technologies and development languages, their responsibilities also include maintaining the performance, integrity, and security of databases across devices.

Data Scientist-

With data innovation such as big data and big data storage at play, there is a growing need for data scientists to sort complex data. Their industry knowledge and deep understanding of machine learning enable them to solve business-related problems using data-driven techniques. From structuring extensive data to determining trends and patterns that scale businesses, a data scientist’s analytical approach explores solutions to significant futuristic issues. 

Data is the key to every business. The voluminous transformation of our data creation and management over the last few decades has been an intriguing development. There was a time when the existence of computers led to the creation of various software that enabled storage and accessing static data. The focus was on minimizing expenses, and there was minimal interest in newer technologies due to a high-risk capacity. As our need for optimal performance and scale developed, so did the heterogeneity of data, which led to the redundancy of traditional DBMS.  

The focus has now shifted to prowess, and the creation of multiple languages and software can help businesses manipulate them. As we started collecting data for everything- weather reports, clients’ files, user behavior, and stock inventory, the perception and purpose of gathering them also modified. There was a sudden uptick among customers for instant responses to the most complex of queries, which made businesses realize that data could be measured to gain lateral information. Hence, companies began looking for options that could revolutionize their data management. Everyone wanted a way to secure their data, enable performance advantages, incur lower costs, and have improved security, as data was now the key to measuring success, understanding consumer metrics, and predicting opportunities. How can one not leverage it in the best way possible? With the dawn of digital dependency, a few years ago, the future of database management shifted to the cloud, with the convergence of the economics of speed and storage. 

Now with the onset of Big Data, BlockChain, and the Internet of Things, one can only imagine the volumes of data being generated by companies. As our demand and supply for connectivity rise continually, the connected devices alone are expected to create about 847 Zettabytes of data per year by 2021. It may sound hypothetical, but it is a fact. According to global industry consultant Boston Consulting Group, automotive data monetization, including connectivity, will grow to $28 billion in business by 2035 from $1 billion today.

Will digital data management become an arduous task? Or will the creation of disruptive advantages create a more prominent noise sufficing every possible whim? Some conversations say quantum supremacy and machine learning are expected to take over as the next big thing. With algorithms and AI leaping forward, there’ll be a significant boost in the future of DBMS; the entire bandwidth will change. There is a possibility that these technologies could completely revolutionize all areas of database management. Keep an eye out!