It's no secret that today's businesses cannot function without data. Think about all the questions you ask yourself at work regularly, "What are my sales so far this month?" "How many customers purchased item X this year?". These questions are answered by data and can provide insights that differentiate a failing company and a successful business. That is why learning to manage databases and make sense of critical data using SQL is such a valuable skill in today's job market.SQL (Structured Query Language) is the primary language responsible for managing data and data structures within a given database. In this article, I will provide an overview of each. Both have many similarities and many differences, which I hope to help you determine which is the best for you to learn or for your company to use. Before I go further, it's essential to explore what an RDBMS is and the language differences.
What is a relational database management system (RDBMS)?
A relational database management system is a program that lets you create, update, and administer a relational database. Most, including MS SQL Server and Oracle Database, use SQL, although Microsoft uses Transact SQL (T-SQL) and Oracle uses Procedural Language SQL (PL/SQL). According to Segue Technologies:
"Both are different 'flavors' or dialects of SQL, and both languages have different syntax and capabilities. The main difference between the two languages is how they handle variables, stored procedures, and built-in functions. PL/SQL in Oracle can group procedures into packages, which cannot be done in MS SQL Server."
While PL/SQL is more complex and has more' capabilities,' T-SQL is simpler and easier to use.
Microsoft SQL Server Overview
Microsoft SQL Server can be used to build, deploy, and manage applications located on-premise or in the cloud. It supports a variety of transaction processing, business intelligence, and analytics applications. Built around a row-based table structure allows related data to be connected, avoiding redundancy and providing greater data integrity. "The core component of Microsoft SQL Server is the SQL Server Database Engine, which controls data storage, processing, and security. It includes a relational engine that processes commands and queries and a storage engine that manages database files, tables, pages, indexes, data buffers, and transactions. Stored procedures, triggers, views, and other database objects are also created and executed by the Database Engine.
" The newest version of Microsoft SQL Server was released June 2016 and included many new features. SQL Server 2016 added performance tuning, real-time operational analytics, data visualization, and mobile device reporting. It also integrated hybrid cloud support that lets DBAs run databases on a combination of on-premises systems and public cloud services to reduce IT costs."
With this recent update, Microsoft has expanded from running exclusively on Windows to being available on Linux, giving users the ability to run SQL Server in Docker containers.
Strengths of MS SQL Server
- Ease of general use (in comparison to other databases)
- Tools like SQL Server Profiler, SQL Server Management Studio, BI tools, and Database Tuning Advisor
- Plenty of online support and documentation, plus live product support
- Option for enterprise-level professional management software
- Ease of data recovery (in comparison to other databases)
How to Learn MS SQL Server
To truly learn this tool's different capabilities, we recommend learning step-by-step with Microsoft SQL Server Virtual labs. While other tutorials may show and tell you about the tool, SQL Server Labs walks you through the steps to perform the tasks yourself, so you can learn by doing.
- Querying Microsoft SQL Server
- Administering SQL Server
- Implementing a Data Warehouse with SQL Server
- Developing SQL Server Databases
- Implementing Data Models and Reports with SQL Server
- Designing Business Intelligence Solutions with SQL Server
- NEW! Administering a SQL Database Infrastructure
Oracle Database Overview
Oracle Database is the first database designed for enterprise grid computing. Enterprise grid computing creates large pools of modular storage and servers.
"With this architecture, each new system can be rapidly provisioned from the pool of components. There is no need for peak workloads because capacity can be easily added or reallocated from the resource pools as needed. The database has logical structures and physical structures. Because the physical and logical structures are separate, the physical storage of data can be managed without affecting the access to logical storage structures."
You can access an Oracle Database only through a client program, and the SQL language is that client program's interface to the Oracle Database. Oracle's latest version of its database was released in June 2013. Users of Oracle databases refer to the server-side memory-structure as the SGA (System Global Area). The SGA typically holds cache information such as data-buffers, SQL commands, and user information. The database also consists of logs, which hold transactional history.
Strengths of Oracle Database
- Ability to upgrade without complete system overhaul
- Option for enterprise-level professional management software
- Ease of data recovery (in comparison to other databases)
- Can handle large amounts of data
How to Learn Oracle Database
Like Microsoft SQL Server, learning to work with databases, especially one as complex as Oracle, requires plenty of practical training, meaning you must learn by doing. One great way to do this is by using a virtual lab. Get a complete walkthrough with the accompanying lab guide to ensure you are completing the steps properly.
Differences Between MS SQL Server and Oracle Database
In general, the Oracle Database is considered to be much more complex than MS SQL Server. That being said, it is meant for larger organizations where a larger database is needed. While the MS SQL Server offers an enterprise version, it is only compatible with Windows and Linux. Oracle can be used on any operating system. One of the biggest differences is transaction control, meaning a group of tasks that can be treated as a single unit. So, suppose a set of records must all be updated simultaneously, by default. In that case, SQL Server executes each command individually, and it will be extremely difficult to make changes if any errors are encountered along the way. Oracle, on the other hand, treats each new database connection as a new transaction. Next is the organization of these databases.
"MS SQL Server organizes all objects, such as tables, views, and procedures, by database names. Users are assigned to a login, which is granted access to the specific database and its objects. Also, in SQL Server, each database has a private, unshared disk file on the server. In Oracle, all the database objects are grouped by schemas, which are a subset collection of database objects, and all the database objects are shared among all schemas and users. Even though it is all shared, each user can be limited to certain schemas and tables via roles and permissions."
In terms of functionality (this is a bit technical), MS SQL Server does not offer partitioning, bitmap indexes, reverse key indexes, function-based indexes, or star query optimization, all of which Oracle offers. Both are widely used across the enterprise landscape, but RDBMS is considered superior as a matter of preference and what that particular database is being used for.
The major distinction between MS SQL and Oracle is the Transaction Control. MS SQL will, by default, perform and commit each job or query separately. Hence, it is not simple or difficult to roll back transactions if any error is encountered in the method. The "Begin Transaction" command is utilized at the start of a transaction for accurate group statements. While the "Commit" statement is employed at the end of the group statement. The modified data is written to the disk and completes the transaction in the Commit statement. In the transaction, any modifications performed within the transaction block are rejected in the Rollback. However, with decent error handling, the rollback command can provide some security against data corruption.
In Oracle, each new database link is interpreted as a new transaction. Until the transaction is committed, the transaction can be rolled back, and all the modifications are performed on the system memory. Due to that, in the rollback, all the variations in the statement can be unhitched. After the commit is fulfilled, typically, the next command starts a new transaction. This serves to check errors efficiently and provide compliance.
MS SQL coordinates all the objects like tables, procedures, and views by database titles. Furthermore, MS SQL databases don't share private disk files on the machine. Users are authorized to login and gain privileged access to the chosen database and its objects. But in Oracle, the database objects are classified by using schemas. Schemas are a segment collection of database objects. All the database objects can be distributed to all users. Schemas and table access can be defined or restricted by roles and permissions.
To Summarize
Companies are always looking for professionals who know how to manage and, most importantly, make sense of data. With relational database management systems like Microsoft SQL Server and Oracle Database taking the enterprise world by storm, it is more important than ever to use these systems. MS SQL Server is ideal for database beginners, while Oracle is optimal for those managing larger amounts of data. In either case, a thorough knowledge of SQL will help you gain insight into customers and products. Browse the Cybrary lab offerings listed above to gain hands-on skills to manage and implement databases and work with powerful reporting tools.
