The digital economy (DE) is a real driver of the business development and innovation. There can hardly be found a company without a website and a bunch of applications for better interaction with clients. Social media, big data, mobile, web and cloud technologies provide many opportunities but require a new approach to software development and data storages. Contemporary business solutions should be agile, fast, highly responsive, always available and ready to process and store huge volumes of various data.

Memory, Applications and Data Structuring

Memory is a resource provided by any computer on a hardware level. Any program requires machine memory to collect, process, record and retrieve information. These operations are performed with the help of APIs on the low level and DBMS on the high level. Since various applications deal with various types and volumes of data, their requirements to data structuring and processing differ markedly.

The most popular approach to the data organization is relational. It is represented with tables with their strict means of relations: columns define data types, rows represent entries, and each row has a unique identifier. Making entries in the table means assigning values to existing attributes and, therefore, creating another data group, another constrained collection. This organization of data according to one model is how SQL structures data in its databases.

The SQL (relational) approach is reliable and efficient for rather homogeneous and consistent data which can be described with a restricted amount of attributes. But the XXI century has brought Web 2.0 with its user-generated content, Internet of things, the developed mobile market etc. This made the variety and volume of contemporary data flows incomparable with the situation of 1970-s, when SQL appeared. Even if some data generally fit the table model, it is very time-consuming to retrieve it from relational databases for a further usage.

What is the NoSQL approach?

The arising DE has challenged the traditional relational approach to databases with its standardized queries and strict data groups. The technology simply turned out to be not ready for huge inconsistent data streams from users and things and too slow for online interactions.

In 2009 enthusiasts ran a conference under the name NoSQL devoted to the search for model-less database solutions and marked the starting point for the whole NoSQL movement. It is complicated to define what is NoSQL, but by now this movement has produced several hundreds of the next generation databases. Most of them are open-source, scalable, non-relational and distributed. They do not share any single model or scheme but can be grouped on the basis of the main data structuring principle:

  • Cloud and Grid Databases;
  • Column Families;
  • Document Store;
  • Event Sourcing Databases;
  • Graph Databases;
  • Key Value;
  • Multidimensional Databases;
  • Multimodel Databases;
  • Multivalue databases;
  • Object Databases;
  • Streaming Databases;
  • XML Databases.

SQL vs NOSQL

For business the database type normally defines the experience their clients go through. Taking into account that more and more of customer engagement happens on the Internet, it is worth understanding which database will suit each company the best. Here is a comparison of NoSQL vs SQL on the basis of the DE principles:

  • Change adoption and innovation are crucial for business development. NoSQL databases are ready to incorporate new data types on the go. Relational databases require changing the whole database model first (together with the relevant applications) and only then allow adding new data types.
  • Contemporary web applications need to serve millions of users and store terabytes of data; and these numbers are constantly growing. This results in very high requirements to servers. SQL databases have to be placed on a single physical server. And its upgrade each time means replacing the current machine with more and more expensive and powerful new equipment. A distributed NoSQL database can increase its resources by simply adding new servers to the existing ones. This is called horizontal scalability.
  • This is already a must that online services are available 24/7. But for relational databases requiring a single physical server it is quite impossible to implement as downtimes during upgrades or system failures are unavoidable. Deploying a database on multiple data centers (possible for NoSQL solutions only) resolves the issue.
  • Due to a 50-year history, the SQL technology has its standards and a huge number of committed professionals. It is considered more reliable than NoSQL solutions at the moment.
  • Technical support. Again, SQL is a well-established and extremely popular technology. Thus, it is easy to find technical support for SQL issues even for free. Complex and sometimes unique NoSQL solutions are much more difficult to get fixed.

The business world has changed dramatically since the birth of Web 2.0. Now any enterprise is a part of the DE; and any customer is expecting a descent experience while using online services. This is the time for companies to sort out their priorities and define the desired outcome of each service. Client engagement, cooperation, interactions and data production require fast and agile NoSQL solutions. While mission-critical applications are better to support with strict and reliable SQL databases.

The article is given by custom software development company VironIT

That’s it! If you have any queries then feel free to ask it in the comment section below.

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