There are numerous implementations of SQL. If you work with data, you are likely left with the question of which SQL instance is best to learn.
Which SQL is best to learn depends on what variant you use at work or certifications that you want to earn since there isn’t one that is best over another when it comes to learning SQL. Due to standardization, different SQL variants will have commonality with similar syntax.
In this article, we will explore the most popular instances of SQL. Additionally, we will analyze why identifying the best SQL for data science, and other fields are more a matter of individual use case scenarios than strict criteria.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
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Which SQL is Most Popular?
If you are currently seeking employment or advancement within a specific company, learning or expanding your knowledge of the particular SQL used in that company’s relational database management system would be the most prudent. You would gain an advantage by learning the nuance that is specific to that version of SQL.
If, on the other hand, you are currently not tied to a specific employer or client, then deciding what SQL to learn may be seen from a more pragmatic angle. For example, what versions of SQL are more popular with companies or sectors that you are interested in serving.
Here is a list of the most popular SQL databases based on data from the 2020 Developer Survey by StackOverflow.
MySQL unsurprisingly tops the list, with over 53 percent of professional developers using MySQL. MySQL databases are commonly found in a wide variety of commercial operations. It is also quite prominent in web hosting environments.
Overall, MySQL is known for its robust security and fast processing of data queries. It is available in both an open-source and proprietary version.
In 2008, MySQL was purchased by Sun Microsystems. Since then, Oracle bought Sun Microsystems and, thus, also assumed ownership of MySQL. For those who prefer applying their skills strictly on open source SQL, the fact that Oracle now owns it may be cause for pause. While there has not been any indication by Oracle that they will make MySQL entirely proprietary, there is concern by some developers that it could happen.
If you fall into that camp, despite MySQL’s immense popularity, that may be a reason to focus on expanding your knowledge on another version of SQL instead.
The second most popular SQL is entirely open source. It is PostgreSQL. In the years preceding 2020, PostgreSQL had not ranked above the third spot.
Its steady and rapid rise in popularity makes it worthwhile to consider learning PostgreSQL in-depth. It is currently used by companies such as Skype, Twitch, and Instagram.
Programmers use PostgreSQL for building applications. Developers use it to create highly secure environments. It provides database administrators with a smoother process for safeguarding the integrity of the data stored.
Additionally, there is no limit on the size of a database with PostgreSQL. There is further flexibility in it being compatible with Windows, Mac OS, and all Linux distributions.
Data mining possibilities are amplified and made easier because PostgreSQL allows you to create custom data types and build custom functions. Code written in other languages, such as Python, does not require you to recompile the database afterward.
If you are keen on open source SQL, wish to latch on to what has demonstrated to be a rising SQL instance, one that is trusted by leading tech companies, PostgreSQL can very well be your best choice of SQL to learn.
Microsoft SQL Server
Microsoft SQL Server databases are relied upon by many well-established companies. Most of these companies rely on Microsoft SQL Server because they rely on other Microsoft products and solutions. Essentially it is used by companies that want to keep as much of their data and information technology within the Microsoft ecosystem.
While this sort of legacy vibe might discourage those who prefer to use open source platforms, there is something to be said about learning a SQL variant that has legacy roots. Having an extended and well-structured development cycle allows for the skills you learn for Microsoft SQL Server to be marketable for a long time.
The companies that rely on Microsoft SQL Server also tend to be those with long-established data management operations. Learning Microsoft Server SQL would allow you to position yourself above other data candidates with recruiters for those companies. If you currently work with a company using Microsoft SQL Server, earning further certifications on the platform can benefit career advancement.
One thing to note is that Microsoft SQL Server relies on T-SQL as its query language. T-SQL is also used with SQL Azure. Learning T-SQL can also benefit you with experience in managing and querying data from cloud-based databases.
SQLite was first developed in 2000. It has experienced steady growth since then. In a survey, just over 30 percent responded as being users of SQLite.
SQLite is open source, and you can even find its source code in the public domain. Similar to PostgreSQL in that regard, SQLite can be of interest to those who prefer open source SQL.
It uses the SQL-92 standard, meaning that learning SQLite will provide you knowledge that readily translates into other instances of SQL.
What About Oracle SQL?
In the Stackoverflow survey, Oracle finished in eighth place, with 16.3 percent professing using it.
Oracle SQL is used to access the Oracle Database Management System. Oracle SQL on its own adheres to the ANSI and ISO standards, so very little difference in command structure is found from other SQLs. However, if you are interested in receiving Oracle certifications, learning Oracle SQL in conjunction with the broader Oracle database management system is ideal.
Like Microsoft SQL Server, if you plan to specialize in working on Oracle databases, this is a worthwhile path for you.
Which SQL is Best for Data Science?
So far, we have expanded upon the SQL instances based on how popular they are among professional developers and data analysts. However, some people will be more interested in determining what SQL is best for data science.
Unlike data analysis, data science relies more heavily on data modeling, algorithms, and machine learning. The purpose is to find patterns and make predictions based on those patterns, not to digest what has happened in the past, such as measuring past performance with key performance indicators.
Data science requires access to more varied sources of data. It includes accessing structured and unstructured databases. Many companies use BitQuery from Google for its multi-cloud data warehouse model. It allows for a massive amount of data to be collected, stored, queried, and used for data science.
BitQuery uses ANSI SQL to query and analyze the data stored on its platform. ANSI SQL is not a specific instance of SQL per se. It is SQL that remains pure to the specifications laid out in the ANSI standards.
As such, for data science purposes, learning SQL through the prism of ANSI specifications would be a proper choice.
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
If you are undecided about what SQL to learn, there isn’t one SQL that is better than another one. Due to standardization by multiple compliance agencies, the difference between different SQLs in syntax and commands is minimal. Knowledge of one is translatable to other SQL instances.
The deciding factors of which SQL to learn resides on collateral factors, such as if you are currently using a specific form of SQL and wish to document your skills and advancement with certifications. Also, the preference for open-source or proprietary platforms can play a role.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
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