What Is an SQL Database?

• SQL Database Definition

  SQL Database Definition

  An SQL database or relational database is a collection of highly structured tables, wherein each row reflects a data entity and every column defines a specific information field. Relational databases use structured query language (SQL) to create, store, update, and retrieve data. SQL is the underlying programming language for all relational database management systems (RDBMSs), such as MySQL, Oracle, and Sybase.
• SQL Database Table Structure

  SQL Database Table Structure

  The SQL database server stores and organizes data in tables. In RDBMSs, tables are fundamental database objects logically designed to collect data into rows and columns. While rows reflect entities, columns define the attributes of each entity. For instance, in a customer data table, each row reflects a record for a specific customer, and each column contains the customer’s information, such as their name and address. The following are key elements of the SQL database table:

  • Columns: Each column holds specific attribute information, and column properties define the data type (e.g., numeric or textual data) and the range it can accept; each table has a primary key to uniquely identify an entity—a specific column (e.g., customer ID) in a customer data table can be the primary key
  • Rows: Database users can add data to each row and execute SQL queries to retrieve data; for the primary key, each row holds a unique value, which helps overcome data duplication challenges

  Example:

  
• How Are SQL Databases Used?

  How Are SQL Databases Used?

  SQL databases are necessary for applications and services across industries. Enterprises rely on SQL database servers for storing and retrieving data. They facilitate a broad range of operational capabilities required to manage business-critical applications, such as transaction processing, analytics, and business intelligence.

  Relational databases contain multiple tables with relevant columns (attributes) and rows (records) and a unique primary key. When the user executes a query, it either updates or modifies the data in the database or retrieves the relevant results for specific queries after checking constraints.

  Users can leverage SQL databases and obtain meaningful information by joining various tables to better understand the context and data relationships. SQL is used to execute basic data management functions and complex queries to transform available raw data into useful and contextual information. Database users can use standard SQLs, such as data definition language (DDL), to create the database and table structures and data manipulation language to insert, update, delete, and select data within the tables.
• SQL Standards and Security

  SQL Standards and Security

  The SQL standard provides the data control language (DCL) commands and structural definitions essential for security.

  1. Access Control (Authentication and Authorization)

  The standard defines the mechanisms for controlling who can access which resources.

  Authorization is managed primarily by the DCL commands GRANT and REVOKE:

  GRANT: This command confers specific privileges (e.g., SELECT, INSERT, UPDATE, or DELETE) regarding specific objects (tables, views, or functions) to a user or role.
  REVOKE: This removes those privileges.

  Users and Roles: The standard defines how individual users and roles (named collections of privileges) are managed to simplify permissions. A user can be assigned to one or more roles.

  Securable Objects: Any database object to which a permission can be applied (tables, views, schema, etc.) is defined as securable.

  2. Data Integrity and Consistency

  Security is not only about keeping intruders out; it's also about ensuring the data within the database is correct, consistent, and uncorrupted.

  Constraints: Defined in the DDL part of the standard, these constraints protect data integrity:

  PRIMARY KEY and UNIQUE: These commands ensure data uniqueness, preventing identity conflicts.
  FOREIGN KEY: This maintains referential integrity between tables, preventing data loss or orphaned records.
  CHECK: This command enforces rules on data values (e.g., a salary must be greater than zero).
  NOT NULL: This ensures critical data is always present.
• Benefits of Using an SQL Database

  Benefits of Using an SQL Database

  Relational databases are a preferred database option for businesses and offer multiple benefits, such as:

  • Higher Flexibility: With SQL as their standard programming language, relational databases leverage DDL to modify the schema seamlessly in real time.; this allows database users to add new tables and columns, rename relations, and implement other changes in real time, without halting any database operations
  • Better Data Consistency: SQL databases maintain data consistency effectively across applications and SQL database server instances, while other database types struggle to maintain real-time consistency for large data volumes; mission-critical applications processing important business transactions rely on relational databases for maintaining data consistency
  • Minimum Redundancy: RDBMSs reduce data redundancy by implementing normalization—with normalization, data is organized to eliminate anomalies related to data insertion, updates, and deletion
  • Performance Optimization: With an array of value-adding features, relational databases help ensure ease and speed of database operations, and minimal memory usage, reduced storage costs, and high processor speeds help accelerate database performance for applications
  • Ease of Maintenance: Automation tools within relational database systems help streamline SQL database repair, control, and maintenance, making it easier for database administrators and technicians to maintain and update the database proactively—external tools for monitoring SQL databases can help manage the database in a customized way for each organization
• SQL Database Performance Metrics

  SQL Database Performance Metrics

  For efficient database performance monitoring and fine-tuning of an SQL database server, a database administrator must proactively track key performance metrics. Enterprises can leverage SQL database analysis tools for more effective database performance management. Tracking metrics helps identify potential issues and anomalies to initiate the appropriate troubleshooting. Below is a list of key metrics to monitor to evaluate whether an SQL database server is performing well:

  • CPU Utilization: This is the most common metric to evaluate the performance of an SQL database server, as it helps analyze memory usage and determine server overload at a given point in time
  • Database Disk Utilization: Measuring database disk usage is an essential component of database performance monitoring; it helps track resource usage and configure alarms and notifications for inefficient resource allocation
  • Page Reads/Minute: This metric evaluates the load on system memory by measuring the number of pages read from memory per minute; analyzing this metric over time helps identify issues with system memory
  • Cache Hit Ratio: This metric measures how frequently an SQL database server accesses pages from the cache: a lower cache hit ratio may suggest a system memory bottleneck; an essential factor impacting cache hit ratio is page life expectancy—long page life expectancy implies the page stays in memory for a long period and results in a better cache hit ratio
  • User Connections: This measures the number of users connected to a database server—long-term analysis of this metric provides insights into memory load patterns and determines other related issues
  • Average Lock Wait Time: SQL database servers manage multiple users at a time; they may reserve resources for specific processes at various intervals, and other processes may need to wait until the resources are released—a higher value for this metric indicates load time issues

  If you are looking to improve the performance of your databases and applications, a performance monitoring tool is a good option. The software provides visibility into the performance of databases and applications, which can help identify and troubleshoot performance problems, optimize database performance, and ensure applications run smoothly.
• SQL Database Types

  SQL Database Types

  Businesses use relational databases ranging from traditional desktop systems to modern cloud-based systems, either open source or commercial closed-source systems. Let’s look at the list of the most used SQL databases.

  MySQL

  MySQL is the most common and easy-to-use open-source SQL database server, and it is widely used for web application development. Besides the open-source version designed to support basic SQL commands and transactions, a commercial enterprise version is also available, which provides an array of extensions and plugins for additional functionality.

  PostgreSQL

  Unlike MySQL and MariaDB, PostgreSQL is an object-relational database management system designed to support more complex and varied data models. It offers many enterprise features, including scalability, security, and better automation support via a command-line interface or direct access over the web. PostgreSQL supports Windows, macOS, and several Linux operating systems. It also supports stored procedures, a highly complex programming language built on top of SQL to facilitate complex transactions and provide atomicity, consistency, isolation, and durability compliance.

  Microsoft SQL Server

  Microsoft SQL Server is another popular relational database whose code is close-sourced and owned by Microsoft. SQL Server supports common Windows and Linux operating systems and facilitates access via SQL queries and graphical user interfaces. Large enterprise applications generally use Microsoft SQL Server instead of an SQL database available in an open-source environment. Enterprises can leverage several features with the current SQL Server version, including referential integrity, multi-version concurrency control, higher availability, fine-grained locking, and greater stability.

  Oracle Database

  Owned by Oracle Corporation, Oracle DB is a commercial, closed-source relational database. It supports macOS, Windows, and Linux operating systems and is effectively used for large applications across industries. An Oracle database can facilitate data and server management automation.
• SQL versus NoSQL Databases

  SQL versus NoSQL Databases

  Unlike SQL databases, NoSQL databases store data in a document format instead of tables. NoSQL databases store nonstructured data, such as photos, videos, and articles, in a single document. Below are some of the key differences between SQL and NoSQL databases:

  • Database Structure: Unlike relational databases, which use tables to store information, NoSQL databases employ a key-value-pairs approach to store all data in one place—in this case, the key indicates a unique element, such as employee email addresses
  • Flexibility: NoSQL databases can store vast amounts of unstructured data without constraints on the types of data users want to keep together—the ability to store different types of data to meet varying needs makes NoSQL databases more intuitive and broadens their scope of application, but they require more processing effort and storage space than relational databases
  • Consistency: Ensuring data availability and consistency is critical to exceptional database performance; while relational databases help ensure consistent data across SQL database server instances, some NoSQL databases, such as Redis, respond to a query with information that may be incorrect by a few seconds

  Professional database monitoring software can monitor a wide range of NoSQL databases, including MongoDB, Redis, Cassandra, and Elasticsearch. It can also monitor applications that interact with NoSQL databases, such as web and business intelligence applications. This visibility can help identify and troubleshoot performance problems, optimize database performance, and ensure applications run smoothly.