5 programming languages database administrators should learn

Database admins strive to ensure that large chunks of data are both accessible and stored with integrity. By using these programming languages, they can keep systems optimized.

As data volumes continue to grow exponentially, so do the complexities of managing them. As such, database administrators are tasked with ensuring the efficient storage, retrieval and management of the complexities that arise from them.

While expertise in database management systems is essential in managing big data, having a solid foundation in some programming languages can significantly enhance a DBA’s skill set and enable them to tackle complex challenges more effectively.

SEE: Download resources for the top programming languages web developers and data admins should know.

Programming languages empower DBAs to automate tasks, optimize queries and develop custom solutions tailored to their organization’s unique needs. Let’s explore five programming languages every database administrator should consider learning in order to stay ahead in the fast-paced world of database management.

Python

Arguably the most popular general-purpose language, Python has its hooks into everything, from systems management and web tools to database management and integration. When paired with established frameworks that plug in functionality, Python can be leveraged to perform data analysis, display and storage — all from one development platform. This shaves down development time and adds increased support from one of the largest support communities.

Difficulty

Python is generally considered an easy-to-learn language due to its clear syntax and readability.

Skills requirements

• Solid understanding of basic programming concepts would be helpful.
• Familiarity with object-oriented programming principles is crucial.

Pros

• Python’s versatility allows it to be used for various tasks, from automation to web development and database management.
• It has a vast ecosystem of libraries and frameworks, making it highly extensible.
• Python’s large community ensures extensive support and resources.

Cons

• Python may not be suitable to use under the limited memory restrictions.
• Python execution is slow as the code is executed line by line.

SEE: Learn more about how Python became the hottest programming language.

SQL

SQL is the de facto standard programming language used by many of the most popular database servers worldwide. While SQL does have its criticisms regarding design, among others, the language is known to be robust and scalable, mixing expressions, queries and statements to produce a wealth of methods to access and extract datasets small and large.

One pitfall to be aware of is, though many different vendors have adopted SQL-based software, not all SQL applications are compatible. There is a known lack of portability between implementations from one SQL developer to the next, which may cause growing pains for users new to DBA.

Difficulty

Due to its relatively straightforward syntax and structure, learners can become acquainted with the fundamentals of SQL within a short period.

Skills requirements

• Familiarity with database management systems and database design is beneficial.
• Knowledge of SQL variants specific to different DBMSs can be advantageous.

Pros

• SQL’s declarative nature allows for efficient querying and manipulation of data.
• Its wide adoption ensures compatibility with various database servers.
• SQL provides a standard interface for interacting with databases.

Cons

• Lack of real-time analytics capabilities.
• Limited flexibility when handling unstructured data.

SEE: Explore the top programming languages mobile app developers should learn.

C#

The C suite of programming languages provides flexibility and efficiency when developing apps that run natively on system hardware. And while it can be leveraged to provide cross-platform support, it can be used to develop applications that interface with relational databases to maximize resources of both the servers hosting the data and systems (or apps) accessing the hosted data. The high-performance nature of native apps is the payoff for the intricate nature of apps developed in C, C++ and C#.

Difficulty

Learning C# can be moderately challenging, especially for those new to programming.

Skills requirements

• Basic understanding of programming concepts is beneficial.
• Prior knowledge of C or C++ can facilitate learning C#.
• Familiarity with object-oriented programming concepts is crucial for leveraging C#’s features effectively.

Pros

• C# allows the development of high-performance native applications.
• C# has an inbuilt garbage collector for managing memory.
• C# integrates well with databases, enhancing data management capabilities.

Cons

• Developing complex applications in C# may require a steeper learning curve.
• Limited use outside of the Microsoft ecosystem may limit its application in certain contexts.

SEE: Explore top programming languages security admins should learn.

R

R is a language whose strengths are based in statistical computing and used widely in data mining, statistical software and data analysis. Given the nature of the datasets used in the above-mentioned types of databases, they tend to be fairly large and complex, making R the perfect language to handle the performance and computational requirements of managing such intricate datasets involving mathematical equations for analysis, display and storing of data.

Difficulty

R can be challenging to learn, particularly for those without any statistical background.

Skills requirements

• Understanding statistical concepts and data analysis principles is crucial.
• Prior experience with programming languages can aid in grasping R’s syntax.

Pros

• R offers extensive statistical and data analysis libraries, making it powerful for research and analysis.
• R is great at handling complex datasets and performing advanced statistical computations.
• R has a strong community and vast online resources for support.

Cons

• R may not be as suitable for general-purpose programming beyond statistical computing.
• It may not have the same level of industry-wide adoption as other languages.

SEE: Explore the top programming languages systems admins should learn.

PHP

While largely co-opted by web developers for complex, interactive websites, PHP has strong ties to databases through its use of server-side scripting to power websites that utilize database connectivity for storing, writing and retrieving records quickly and efficiently.

For example, the WordPress platform was built on PHP, and it has tight integration with databases to streamline web development, build websites based on a templating system and aid HTML-based sites in loading faster across all supported platforms and apps.

Difficulty

PHP is relatively easy to learn if you have prior web development experience.

Skills requirements

• Understanding web development principles and concepts is important to learning PHP.
• Knowledge of SQL and database connectivity is key.

Pros

• PHP has built-in functions and extensions that aid integration with database management systems like MySQL, PostgreSQL and Oracle.
• PHP is open-source and free to use, which makes it a cost-effective solution for organizations.

Cons

• PHP’s historical design quirks and inconsistencies can lead to unexpected behavior.
• It may not be as suitable for non-web-related programming tasks.

Knowing when to use the right programming language

Knowing when to use the right programming language is crucial for efficient and effective database administration. You want to use a language with strong database connectivity and efficient data handling capabilities. It’s also important to take into account the scalability and future growth of your database systems and how the programming language you want to use can support them.

Additionally, considering industry standards and widely adopted database management systems helps ensure compatibility and access to relevant resources. Taking cognizance of the learning curve and availability of resources, such as comprehensive documentation, active community forums and specific libraries or frameworks for database management tasks, is also crucial.