SQL Database Definition

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 are built using the structured query language (SQL) to create, store, update, and retrieve data. Therefore, SQL is the underlying programming language for all relational database management systems (RDBMS) such as MySQL, Oracle, and Sybase, among others.

SQL database table structure

SQL database server stores and organizes data in tables. In RDBMS, tables are fundamental database objects logically designed to collect data in rows and columns format. 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 table column contains corresponding customer information, like the customer’s 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 (for example, numeric or textual data) and range it can accept. Each table has a primary key to uniquely identify an entity. A specific column, for example, 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 also helps overcome data duplication challenges.

How are SQL databases used?

SQL databases serve as a cornerstone for several applications and services across industries. Enterprises rely on SQL database servers for storing and retrieving data as it facilitates a broad range of operational capabilities, including transaction processing, analytics, and business intelligence required to manage business-critical applications.

Relational databases contain multiple tables with relevant columns (Attribute) and rows (Record) along with 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 to get meaningful information by joining various tables to understand the context and data relationships better. 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 SQL languages such as data definition language (DDL) for creating the database and table structures and data manipulation language (DML) to insert, update, delete, and select data within the tables.

Benefits of using SQL database

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

• Higher Flexibility: With SQL as its standard programming language, relational databases leverage its DDL to modify the schema seamlessly in real time. It allows database users to add new tables and columns, rename relations, and implement various 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. Other types of databases struggle to maintain real-time consistency for large data volume. Mission-critical applications processing important business transactions rely on relational databases for maintaining data consistency.
• Minimum Redundancy: RDBMS reduces data redundancy by implementing normalization. With normalization, data is organized to eliminate anomalies related to data insertion, update, and deletion.
• Performance Optimization: With an array of value-adding features, relational databases ensure ease and speed of performing database operations. Minimum memory usage, reduced storage costs, and high processor speed help accelerate database performance for all applications.
• Ease of Maintenance: Built-in automation tools within the relational database systems help streamline SQL database repair, control, and maintenance. It makes it easier for database administrators and technicians to maintain and update the database proactively. In addition, the use of external tools for monitoring SQL databases can provide the opportunity to manage the database in a customized way for each organization using databases.

SQL database performance metrics

For efficient database performance monitoring and fine-tuning of SQL database server, a database administrator must proactively track key performance metrics. Enterprises can benefit from leveraging SQL database analysis tools for more effective database performance management. Tracking metrics helps in identifying potential issues and anomalies to initiate adequate troubleshooting. Here’s the list of key metrics to monitor and evaluate if a SQL database server is performing well:

• CPU Utilization: The most common metric to evaluate the performance of a 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/Min: Evaluates the load on system memory by measuring the number of pages read from memory per minute. Analyzing this metric over time helps in identifying whether there are issues with system memory.
• Cache Hit Ratio: Measures how frequently a 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 long and results in a better cache hit ratio.
• User Connections: Measures the number of users connected to a database server. Long-term analysis of this metric provides insights into the memory load patterns and promptly determines other related issues.
• Average Lock Wait Time: SQL database server manages multiple users at a given point in time. Therefore, it may reserve resources for specific processes at various intervals, and other processes may have to wait until the resources are released. A higher value for this metric indicates load time issues; therefore, it's recommended to ensure the value for this metric stays closer to zero.

SQL database list

Most 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 most used SQL databases.

MySQL

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

PostgreSQL

Unlike MySQL and MariaDB, PostgreSQL is an object-relational database management system (ORDBMS) designed to support more complex and varied data models. It offers a range of 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 distributions. It also supports stored procedures, a highly complex programming language built on top of SQL to facilitate complex transactions and provide ACID (Atomicity, Consistency, Isolation, Durability) compliance.

Microsoft SQL Server

Microsoft SQL Server is another most 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 vs. SQL databases available in an open-source environment. Enterprises can leverage a range of 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 vs. NoSQL databases differences

In contrast to SQL databases, NoSQL databases store data in a document format instead of tables. NoSQL databases store non-structured data such as photos, videos, articles, and more in a single document. Below are a few of the key differences between SQL and NoSQL databases:

• Database Structure: Unlike relational databases with 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, for example, an email address for employees.
• Flexibility: NoSQL databases can store vast amounts of unstructured data without constraints on the types of data users want to keep together. Flexibility in storing different new types of data as per the varying needs makes NoSQL databases more intuitive and broadens the scope of application. However, databases require extra processing effort and more storage than relational databases.
• Consistency: Ensuring data availability and data consistency are critical aspects to ensure exceptional database performance. While relational databases always 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.