The Dilemma: Whether or Not to Use SQL

Just like Prince Hamlet’s famed soliloquy, selecting the appropriate database – either relational or non-relational – for your application is a complicated decision with significant implications. Our aim is to provide an in-depth comprehension of the factors involved in determining the optimal database for your upcoming project and the relevance of using SQL.

What are the benefits of SQL?
Developers at IBM Corporation introduced Standard Query Language (SQL) in the 1970s, initially dubbed “SEQUEL”. Dr. Edgar Codd’s publication, “A Relational Model of Data for Large Shared Data Banks,” which is universally recognised as the standard for Relational Database Management Systems (RDBMSs), provided a foundation for SQL’s creation. Dr. Codd aimed to implement Relational Theory into data management to reduce end-user involvement in data organisation decisions.

In response to the restrictions of SQL for managing the vast amounts of data and complex IT infrastructure demanded by Web 2.0 companies like Facebook, NoSQL was introduced. ‘Big Data’ refers to a large data set with substantial volume, velocity, and variety.

Twitter was estimated to handle more than 500 million messages per day, or about 6,000 tweets each second, by 2022. An RDBMS would likely be incapable of handling the volume, variance, and precision of this data. The speed of extracting value from vast amounts of data is a significant factor in determining its value to a company.

In recent years, prominent companies have identified the imperative for NoSQL systems like Cassandra, DynamoDB, and BigTable, which were created by Amazon and Google. Since then, Veracity and Value have been recognised as two additional Vs of Big Data, and non-relational databases prioritising consistency, performance, and reliability have gained traction.

Relational Databases in Management Information Systems

Keys are a crucial element of SQL databases and relational database management systems, facilitating the linkage of information across tables. To link a row in one table to the data of another table, a key is necessary. For example, the key in the ‘STUDENTS’ table’s ‘tutor’ column will point to a row in the ‘TUTORS’ table, and this key, such as an email address, may or may not be the primary key of the ‘TUTORS’ table, but it must be present to ensure the table’s uniqueness. The key in the ‘STUDENTS’ table is a foreign key that is utilised to connect data from multiple tables.

SQL databases necessitate a fixed and pre-established structure, along with the presence of connections between tables. The schema lays out certain data configurations, such as specifying that a specific column must always be of type INTEGER or that a specific table can only have four columns.

Oracle, MySQL, Microsoft SQL Server, SQLite, and PostgreSQL are among the relational databases.

Characteristics of Relational Databases

  1. Storage of data fields in tables
  2. Strictly defined structures
  3. SQL Queries:

Advantages of Utilising a Relational Database

  1. Through the utilisation of primary and foreign keys, RDBMS achieves data consistency, a characteristic known as “referential integrity”. Constraints are used to ensure data accuracy and consistency. For instance, an attempt to delete a primary record referenced by foreign keys will fail. SQL has various rules to handle such situations. These consist of “ON DELETE CASCADE,” which deletes all linked objects, “ON DELETE RESTRICT,” which permits deletion only if the foreign key is referenced in the same operation, “ON DELETE PROTECT,” which forbids the deletion of referenced objects, “ON DELETE SET NULL,” which sets the Foreign Key null, and “ON DELETE SET NULL”.
  2. Database integrity is protected by the ACID principles of atomicity, consistency, isolation, and durability.
  3. Normalization is a technique employed to minimise repetitive data in SQL databases. To achieve this, large tables are broken down into more manageable parts.
  4. Proficiency in constructing complex SQL queries, which is useful for data analysis.

Issues with Using Relational Databases

  1. Vertical scalability is feasible in SQL databases, but it may be necessary to upgrade hardware and processing resources as the quantity of data stored increases in order to accommodate larger data sets. Furthermore, handling complicated queries on relational databases necessitates a substantial amount of computing power.
  2. Relational Database Management Systems (REBMS) abide by a stringent data structure. As a result, any adjustments to the data source will necessitate a review of the data model, which includes existing records.

Separate Data Storage Systems

Non-Relational databases contrast with RDBMS in their non-structured nature. Since they do not depend on a predefined data model, they are adaptable to handle new or altered structures efficiently. Rather than concentrating on record relationships, they are developed to fit the kind of data they are expected to store. The most typical storage structures employed by NoSQL databases include key-value, document, graph and column-oriented.

Key-Value Stores Implementation

Through the use of a hash table, a distinct piece of data can be located using a one-of-a-kind key. To enhance comprehensibility, the keys can be classified into separate logical groups. Key-value stores are widely utilised, with Redis being one example.

Archive Systems for Records

Unlike key-value stores, certain databases also offer the ability to encode data. Popular encoding formats include JSON, BSON and XML, which allows for querying of both the data and keys. MongoDB and ElasticSearch are two databases that offer this functionality.

Databases Employing Graph Data Storage

A directed graph structure consisting of nodes and edges is a prevalent method for visualising data. Graph stores have grown in popularity as social networking applications shift their focus from the products themselves to the relationships between them. Neo4J and Graph Base are two examples of such programmes.

Stores Arranged in Columnar Styles

The NoSQL method stores data in columns rather than the conventional row-based approach of relational database management systems. By storing each column’s rows as separate disc entries, this method facilitates rapid reads and writes. Column stores are steadily increasing in popularity, two prominent implementations being Cassandra and BigTable.

Advantages of Utilising NoSQL Databases

  1. Non-relational databases, unlike relational database management systems (RDBMS), do not necessitate a pre-established data structure (the schema) to function.
  2. Through the addition of supplementary devices, such as cloud servers, to handle queries, horizontal scalability can boost throughput.
  3. Operating a Relational Database Management System (RDBMS) necessitates the presence of a skilled SQL specialist for maintenance and management. On the other hand, a NoSQL database offers data distribution as well as automated repairs, lowering the demand for manual administration.

Effects of Employing a NoSQL Database

  1. Since NoSQL databases do not utilise ACID characteristics, ensuring data consistency and integrity becomes impossible. Custom-built logic is required to produce comparable results, which might potentially add complexity.
  2. Non-relational database management systems (NoSQL) do not have a universal language, making it difficult to shift between databases. Relational Database Management Systems (RDBMS) utilise Structured Query Language (SQL) to create queries, but each NoSQL database has its own query language. Thus, a programmer familiar with MySQL would find it simpler to move to PostgreSQL as opposed to ElasticSearch.

SQL, To Be or Not To Be?

Both relational database management systems and NoSQL databases have been created to resolve data management dilemmas. Thus, proposing that one form is inherently superior to the other is not wise. The preferred storage format should be selected based on business requirements and the data being stored. For example, a social networking app dealing with the 5 Vs would most likely opt for a NoSQL database due to its flexibility, whereas a school with a static enrolment of 300 students might choose a SQL database. While future business demands should be considered, present circumstances are equally crucial. If rapid scalability is necessary in the near future, a NoSQL database may be the most suitable choice.

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