What is SQL and how does it work?

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What is SQL and how does it work?

SQL is the most common language for extracting and organising data that is stored in a relational database. A database is a table that consists of rows and columns. SQL is the language of databases. It facilitates retrieving specific information from databases that are further used for analysis.

Relational databases have been the industry standard since the late 1970s, though many of their “navigational” predecessors (e.g., Apollo 11-era IMS) are still under active development. In fact, most current enterprise systems architecturally descend from the aforementioned System R.

SQL databases: Pros and cons

Pros :

  1. Faster Query Processing – Large amount of data is retrieved quickly and efficiently. Operations like Insertion, deletion, manipulation of data is also done in almost no time.

  2. No Coding Skills – For data retrieval, large number of lines of code is not required. All basic keywords such as SELECT, INSERT INTO, UPDATE, etc are used and also the syntactical rules are not complex in SQL, which makes it a user-friendly language.

  3. Standardized Language – Due to documentation and long establishment over years, it provides a uniform platform worldwide to all its users.

  4. Portable – It can be used in programs in PCs, server, laptops independent of any platform (Operating System, etc). Also, it can be embedded with other applications as per need/requirement/use.

  5. Interactive Language – Easy to learn and understand, answers to complex queries can be received in seconds.

cons :

  1. Complex Interface – SQL has a difficult interface that makes few users uncomfortable while dealing with the database.

  2. Cost – Some versions are costly and hence, programmers cannot access it.

  3. Partial Control – Due to hidden business rules, complete control is not given to the database.

What is NoSQL?

NoSQL, also referred to as “not only SQL”, “non-SQL”, is an approach to database design that enables the storage and querying of data outside the traditional structures found in relational databases.

Research on non-relational systems (e.g., BigTable and Dynamo) led to the rise of startups and open source projects dedicated to increasing the relational model’s horizontal scalability and loosening the rigidity of its table design. Their emergence revealed a need for better designs and looser constraints for relational databases.

NOSQL: Pros and cons

Pros:

  1. Flexible Scalability Unlike rational database management model that is difficult to scale out when it come to commodity clusters NoSQL models make use of new nodes which makes them transparent for expansion. The model is designed to be used even with low cost hardwares. In this current world where outward scalability is replacing upwards scalability, NoSQL models are the better option.

  2. Stores Massive Amounts Of Data Given the fact that transaction rates are rising due to recognition, huge volumes of data need to be stored. While rational models have grown to meet this need it is illogical to use such models to store such large volumes of data. However these volumes can easily be handled by NoSQL models

  3. Database Maintenance The best rational models need the service of an expert to design, install and maintain. However, NoSQL models need much less expert management as it already has auto repair and data distribution capabilities, fewer administration and turning requirements as well as simplified data designs.

Cons:

  1. Not Mature Rational models have been around for some time now compared to NoSQL models and as a result they have grown to be more functional and stable systems over the years.

  2. Less Support Every business should be reassured that in case a key function in their database system fails, they will have unlimited competent support any time. All rational model vendors have gone the extra mile to provide this assurance and made it sure that their support is available 24 hours which is not a step yet guaranteed by NoSQL vendors.

  3. Business Analytics And Intelligence NoSQL models were created because of the modern-day web 2.0 web applications in mind. And because of this, most NoSQL features are focused to meeting these demands ignoring the demands of apps made without these characteristics hence end up offering fewer analytic features for normal web apps.