What is SQL Database?
Get an overview of SQL technology, benefits, and use cases.
SQL database definition
SQL databases, also known as relational databases, are systems that store collections of tables and organize structured sets of data in a tabular columns-and-rows format, similar to that of a spreadsheet. The databases are built using structured query language (SQL), the query language that not only makes up all relational databases and relational database management systems (RDBMS), but also enables them to “talk to each other”.
Why do SQL Databases exist?
The history of database technology / relational databases
SQL was invented as a language in the early 1970s, which means SQL databases have been around for as long as the Internet itself. Dubbed the structured English query language (SEQUEL), SQL was originally created to streamline access to relational database systems and to assist with the processing of information. Today, SQL remains one of the most popular and widely used query languages in open-source database technology due to its flexibility, ease of use, and seamless integration with a variety of different programming languages. You’ll find SQL being used throughout all types of high-performing, data-centric applications.
What’s the difference between SQL and NoSQL databases?
SQL databases organize data in columns and rows. The rows contain data sets that apply to each item, while the columns define the different properties of those items, such as product ID, name, quantity, and unit price. In contrast, NoSQL databases store all incoming data in a single document with no overt structure. This makes SQL databases conducive to storing structured forms of data while NoSQL databases are equipped to handle large volumes of structured, semi-structured, and unstructured data from non-traditional sources.
Below, you will find key differences between SQL and NoSQL databases.
| Features | SQL | No SQL |
|---|---|---|
| Types of data | Structured | Structured, semi-structured, unstructured |
| Types of databases | Relational | Relational and non-relational |
| Structure or schema | Tables | Document |
| Data format | Processed | Raw |
| Flexibility | Low | High |
| Availability | High | Low |
| Sources | Applications, transactional data, batch reporting, BI | Big data, IoT, social media, streaming data |
Benefits of using SQL databases
Now you know what an SQL database is and how it functionally differs from a NoSQL database. But why do organizations use relational databases, and in what situations do they use them? SQL databases offer countless benefits that make data management easy, including:
- Optimized performance. Due to high processing speeds and minimal storage usage, relational databases can retrieve enormous batches of data transactions in near-real time, then insert, delete, or modify that data almost instantly.
- Seamless collaboration. With an SQL database, you have the ability modify the schema in real time. This means any user can add, remove, and modify the data inside each column and row, or even remove the columns and rows themselves, all without disrupting the workflow of other users.
- Clean, reliable data. SQL databases not only maintain consistency across all server instances, but they also reduce redundancies in the data related to insertions and deletions—which is essential for maintaining accuracy and speed when processing a large batch of transactions.
- Easy to access and learn. SQL is written in plain English and not in complex code, which makes it easier for the average user to select, insert, update, and delete data, so long as they learn the functions and the syntax.
- Community support. Because SQL is an open-source language, it is supported by a worldwide community of developers who provide continuous updates, documentation, and troubleshooting help when the need arises.
Common use cases for SQL databases
In a data-centric world, SQL databases run the show. Software companies, banks, government agencies, universities, and organizations from different industries rely on relational databases to store records, manage data, and perform important business operations. Here are just a few use cases out of many:
- Mission-critical applications. Financial systems, payment processors, and other mission-critical apps that are working with highly structured, centralized data use SQL technology to support transactions—and provide an added layer of security along the way.
- Business intelligence. Across a wide range of industries, BI analysts use relational databases to pull reports and make them available to operations, HR, sales, warehousing, and marketing departments for further analysis and decision-making.
- Data integrity. Apps that work with private, sensitive data sets rely on SQL technology to set well-defined constraints, avoid data duplication, and establish data integrity. This ensures that the data not only remains reliable and secure, but also complies with standards of atomicity, consistency, isolation, and durability (ACID), also known as ACID compliance.
- Other types of apps. Apps that handle high volumes of structured data sets, but aren’t always required to be on, rely on SQL databases to support periodic scaling and growth.
Types of databases
Now that you know the benefits and applications of SQL databases, let’s get an overview of the different types and how they differ from each other.
First, you’ll want to determine when to choose a relational database over a nonrelational database and vice-versa. Because SQL databases are structured, they are perfect for handling transactions, records, and libraries. NoSQL databases have the capacity to support all forms of data, including texts, images, IoT notifications, and other forms of big data. Both SQL and NoSQL databases make their respective forms of data readily available for search and analysis.
Let’s look at some commonly used SQL and NoSQL databases:
- SQL Server. SQL databases services are typically built on a relational database management system—and many enjoy the capabilities of cloud computing. Azure SQL, for instance, is a family of managed SQL database services built on the SQL Server database engine and hosted in the Azure cloud.
- PostgreSQL. PostgreSQL is an advanced object-relational database management system (ORDBMS) that stores and scales workloads that are too complex to be supported by your standard systems. A cloud-based service for PostgreSQL, like Azure Database for PostgreSQL, offers additional enterprise features and extensibility, as well as the support of PostgreSQL’s open-source community.
- MySQL. MySQL is one of the most popular, widely used open-source relational database management systems in modern app development. Unlike SQL, MySQL is a piece of software, not a language. A managed MySQL database service, like Azure Database for MySQL, lets you provision a database in minutes and scale just as quickly.
- NoSQL. NoSQL database services enable users to develop modern, responsive, high-performance apps at any size or scale. They also support a wide variety of open-source databases. Azure Cosmos DB supports PostgreSQL, MongoDB, and Apache Cassandra, is fully managed, auto-updates, and auto-scales.
The future of SQL
The future of SQL is in the cloud, which is why many organizations are now opting for cloud databases over traditional, on-premises solutions. A cloud database is a database service that’s been built and hosted on a cloud platform, providing the same functionality as an on-premises server, but with the infrastructure and scalability of cloud computing.
Here’s how cloud databases compare to on-prem:
- Managed services. A fully managed cloud database-as-a-service streamlines and automates updates, backups, provisioning, and other configuration tasks so that you can focus on developing high-performance apps.
- No hardware required. Organizations can now enjoy the benefits of an SQL database without having to buy the dedicated server hardware to support it. And by hosting in the cloud, your database will always update to the latest version of SQL.
- More flexibility. While most on-premises SQL databases can only support relational databases like MySQL and PostgreSQL, cloud databases can support SQL databases and NoSQL databases, including MongoDB and Apache CouchDB.
- Easier access. SQL databases are generally easy to access, but users now have the ability to access a cloud database with even more ease through a vendor API or web interface.
- Cost-saving scalability. Cloud databases can scale up or down depending on an organization’s usage requirements, allowing them to only use the resources they need, and to only pay for what they use.
- Disaster recovery. With the help of remote server backups, cloud databases remain available and secure, even when disaster strikes, and the power goes out.
Get started with Azure SQL
Learn more about cloud databases—and try one out for yourself. Part of the Azure SQL family, Azure SQL is a fully managed relational database service built for the Azure cloud. Build your next app with the assistance of a fully managed SQL database with built-in AI capabilities, auto-scaling, and backups.
Additional resources
Frequently asked questions
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Structured query language (SQL) is the programming language that makes up all SQL databases, also known as relational databases, which store and process highly structured data in tabular rows and columns, much like that of a spreadsheet.
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A cloud database is a database service that’s hosted and accessed through the cloud, which means that in addition to reaping the benefits of SQL, a cloud database also enjoys the managed services, flexibility, and scalability that comes with cloud computing.
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While SQL is a very accessible language for non-coders, you should have a solid understanding of how data typically functions in an organization. To take full advantage of what an SQL cloud database has to offer, you may want to familiarize yourself with basic data concepts, analytics, roles, services, and products.