If it’s your first time learning SQL, then you may have come across a lot of SQL augmented terms such as MySQL, PostgreSQL, SQL Server and so. You may be wondering how the SQL you might be learning is different from these.
Well it’s time to differentiate among those SQL specific terms but first let’s learn some history.
SQL started long ago
The Structured Query Language- or Sequel as we pronounce it, has been here since the 1970s and developed by two IBM researchers: Raymond Boyce and Donald Chamberlin. The two coworkers developed the programming language to store, access and manipulate data specifically in relational databases.
Just a few years before the creation of SQL, a scientist Edgar Frank Codd published a paper titled: ‘A Relational Model of Data for Large Shared Data Banks’ in 1970. Codd’s paper proposed the idea of storing data into a database in the form of relations, that is, the tables. These tables are then linked to each other forming relations.
And so, IBM’s first relational database, the System R, used SQL to store, retrieve, and manipulate data from within the relational database.
Evolution of SQL
The SQL we see today has evolved from IBM’s first Sequel which was later commercialized in 1979 by Oracle (then known as Relational Software) as Oracle V2 to the-best-in-class SQL supporting window and aggregate functions.
The American National Standards Institute (ANSI) and the International Organization for Standardization (IOS) have termed SQL as the standard language in relational database communication.
Today, as the businesses are increasingly storing data they produce and receive to extract value from it later, there are a number of tech companies out there which offer relational database and database management services. These services use the ANSI SQL along with some additional company developed SQL functionalities to enable the database’s additional operations.
Businesses produce large amount of transactional data that could be financial or non-financial through their deployed operational systems. These operational systems use OLTP: Online transaction processing tools to support huge transactions from a large number of users in real-time.
OLTP systems use basic SQL commands such as INSERT, DELETE, and UPDATE clauses. Example of a transaction from an OLTP system of sales point is the information of products purchased by a customer.
Transactions from a single OLTP system if used for analysis and reporting then need OLAP (online analytical processing) tools that utilizes advanced SQL statements.
What’s a database management system?
Many corporations provide a software application to manage a database, known as a database management system- DBMS. A relational DBMS- RDBMS is a computer that processes the SQL statements originated from a client application (such as a SQL terminal) and has the specifications of fault tolerance and authoritative access.
Then there are some non-traditional database management systems (to manage non-relational databases) which don’t rely on Codd’s relational database theory. Ironically, these DBMS also use their own versions of SQL.
Popular in the list
The most production grade applications are provided by the following four RDBMS in the market.
MySQL
First in the list is MySQL which is a database management system developed by Oracle Corporation. It’s an open-source software application that is designed for creating, storing, and manipulating data within a database in an efficient manner.
MySQL along with offering data management services also offers a database server for storage service, which uses standard SQL (ANSI- 92) as well as some additional SQL statements uniquely used for MySQL DBMS.
MySQL is efficient in read transactions and saves companies query processing time. For this reason, it’s mostly used in web applications to support high-volume traffic. You might also find its application in data warehousing, and e-commerce.
“We see huge companies using the database including Facebook, Twitter, Google, and Adobe”.
MySQL is compatible with other databases such as NoSQL databases (that are non-relational databases and are based on document design), and cloud databases.
Earlier versions of MySQL only supported OLTP processing, but now the new version also supports OLAP for data analysis and reporting.
MySQL is ranked second in the list of top performing DBMS 2022.
PostgreSQL
Second in the list is PostgreSQL, aka Postgres, and is one of most popular relational database management systems after MySQL It was developed in 1986 by a team of computer scientists at the University of California at Berkeley.
PostgreSQL, just like MySQL is an open source DBMS but carries additional features such as ability to write software applications using object oriented programing languages such as C++ and Java. Unlike MySQL it has its own procedural language called PL/pgSQL.
That’s why it’s also called ‘object relational database management system’.
Apart from data management, and protecting data integrity, you can use PostgreSQL to write code in other programming languages to process complex queries and build software applications.
PostgreSQL is an enterprise wide DBMS and supports complex queries and frequent read and write transactions, and therefore might be considered better for organizations that aim to scale up their applications in future. MySQL on the other hand is better at processing frequent read transactions only.
“Netflix and Instagram use Postgres DBMS”.
Postgres offers more data types than MySQL, these are called abstract data types and thus offers more functionality for the developer.
It allows for a separate library of geospatial SQL queries with its PostGIS extension.
Postgres also supports querying from materialized views (a data object that is the result of a query).
There is a single analytical engine for both OLTP and OLAP processing (HTAP: Hybrid Transaction/Analytical Processing).
Postgres is ranked fourth in the list of top performing DBMS 2022.
Oracle
As part of the information management, Oracle is the top performing database in the market with first rank in the DBMS 2022 rankings.
It uses the enterprise grid computing model to offer storage or server resources making it a flexible and cost effective solution for information management. Depending on the workload, new storage or server resources could be added from a pool of industry standards.
“Zoom uses Oracle to support millions of online meetings in the covid era. Oracle’s DBMS enabled Zoom to scale up its services to such a huge number of customers”.
That’s how grid computing database service makes Oracle one of the most resilient databases out there.
It has strict ACID compliance: ACID are the principles that ensure transactions are processed reliably (ACID: atomicity, consistency, isolation and durability).
It supports all Analytical and window functions and has its own procedural language PL/SQL thus additionally offers application development too.
It’s closed source and is not available for free. Oracle has an immensely rich feature set which increases the cost of upgrading. This is the reason why MySQL and PostgreSQL are more common than Oracle databases.
SQL Server
SQL Server is developed by Microsoft with its first version released in 1989. It supports similar performance standards like Oracle but with some unique features such as its own procedural T-SQL, and a query store that lets you optimize the query performance.
Not just the management of data is handled by SQL server, the RDBMS also offers business intelligence BI tools and offers reporting services on the data through its SQL Server Analysis Services.
“The fintech dv01 shifted from Postgres to SQL Server to enable faster processing of complex queries”.
It’s ranked 3rd in the list of top performing DBMS in 2022 rankings. Compared to Oracle, a rich feature set version of SQL Server is available for free.
SQL is everywhere, let’s learn it!
Now that you realize the power of SQL in database management and that it will continue to evolve over the distant future as more and more companies continue adopting a data driven approach, learning this core skill could land you on a promising career.
There’s good news for you!
SQL is easy to understand compared to other procedural languages with its simple and human-friendly syntax.
There are a bunch of SQL courses out there for free that will help you get hold of the basic SQL queries. Popular platforms include Codecademy and DataCamp. But if you lack a systematic and comprehensive course outline then our experts at Dice Analytics can offer you hands-on training to become an SQL expert.
You might choose among different options as per your need, from learning SQL in RDBMS market leader SQL Server, or using Teradata SQL for Data warehouse applications.
