A database is an organized collection of structured information, or data, typically stored electronically in a computer system. A database is usually controlled by a database management system (DBMS). Together, the data and the DBMS, along with the applications that are associated with them, are referred to as a database system, often shortened to just database.
Data within the most common types of databases in operation today is typically modeled in rows and columns in a series of tables to make processing and data querying efficient. The data can then be easily accessed, managed, modified, updated, controlled, and organized. Most databases use structured query language (SQL) for writing and querying data.
SQL is a programming language used by nearly all relational databases to query, manipulate, and define data, and to provide access control. SQL was first developed at IBM in the 1970s with Oracle as a major contributor, which led to implementation of the SQL ANSI standard, SQL has spurred many extensions from companies such as IBM, Oracle, and Microsoft. Although SQL is still widely used today, new programming languages are beginning to appear.
Databases have evolved dramatically since their inception in the early 1960s. Navigational databases such as the hierarchical database (which relied on a tree-like model and allowed only a one-to-many relationship), and the network database (a more flexible model that allowed multiple relationships), were the original systems used to store and manipulate data. Although simple, these early systems were inflexible. In the 1980s, relational databases became popular, followed by object-oriented databases in the 1990s. More recently, NoSQL databases came about as a response to the growth of the internet and the need for faster speed and processing of unstructured data. Today, cloud databases and self-driving databases are breaking new ground when it comes to how data is collected, stored, managed, and utilized.
Databases and spreadsheets (such as Microsoft Excel) are both convenient ways to store information. The primary differences between the two are:
Spreadsheets were originally designed for one user, and their characteristics reflect that. They’re great for a single user or small number of users who don’t need to do a lot of incredibly complicated data manipulation. Databases, on the other hand, are designed to hold much larger collections of organized information—massive amounts, sometimes. Databases allow multiple users at the same time to quickly and securely access and query the data using highly complex logic and language.
There are many different types of databases. The best database for a specific organization depends on how the organization intends to use the data.
These are only a few of the several dozen types of databases in use today. Other, less common databases are tailored to very specific scientific, financial, or other functions. In addition to the different database types, changes in technology development approaches and dramatic advances such as the cloud and automation are propelling databases in entirely new directions. Some of the latest databases include
Database software is used to create, edit, and maintain database files and records, enabling easier file and record creation, data entry, data editing, updating, and reporting. The software also handles data storage, backup and reporting, multi-access control, and security. Strong database security is especially important today, as data theft becomes more frequent. Database software is sometimes also referred to as a “database management system” (DBMS).
Database software makes data management simpler by enabling users to store data in a structured form and then access it. It typically has a graphical interface to help create and manage the data and, in some cases, users can construct their own databases by using database software.
A database typically requires a comprehensive database software program known as a database management system (DBMS). A DBMS serves as an interface between the database and its end users or programs, allowing users to retrieve, update, and manage how the information is organized and optimized. A DBMS also facilitates oversight and control of databases, enabling a variety of administrative operations such as performance monitoring, tuning, and backup and recovery.
Some examples of popular database software or DBMSs include MySQL, Microsoft Access, Microsoft SQL Server, FileMaker Pro, Oracle Database, and dBASE.
MySQL is an open source relational database management system based on SQL. It was designed and optimized for web applications and can run on any platform. As new and different requirements emerged with the internet, MySQL became the platform of choice for web developers and web-based applications. Because it’s designed to process millions of queries and thousands of transactions, MySQL is a popular choice for ecommerce businesses that need to manage multiple money transfers. On-demand flexibility is the primary feature of MySQL.
MySQL is the DBMS behind some of the top websites and web-based applications in the world, including Airbnb, Uber, LinkedIn, Facebook, Twitter, and YouTube.
With massive data collection from the Internet of Things transforming life and industry across the globe, businesses today have access to more data than ever before. Forward-thinking organizations can now use databases to go beyond basic data storage and transactions to analyze vast quantities of data from multiple systems. Using database and other computing and business intelligence tools, organizations can now leverage the data they collect to run more efficiently, enable better decision-making, and become more agile and scalable. Optimizing access and throughput to data is critical to businesses today because there is more data volume to track. It’s critical to have a platform that can deliver the performance, scale, and agility that businesses need as they grow over time.
The self-driving database is poised to provide a significant boost to these capabilities. Because self-driving databases automate expensive, time-consuming manual processes, they free up business users to become more proactive with their data. By having direct control over the ability to create and use databases, users gain control and autonomy while still maintaining important security standards.
Today’s large enterprise databases often support very complex queries and are expected to deliver nearly instant responses to those queries. As a result, database administrators are constantly called upon to employ a wide variety of methods to help improve performance. Some common challenges that they face include:
Addressing all of these challenges can be time-consuming and can prevent database administrators from performing more strategic functions.
Self-driving databases are the wave of the future—and offer an intriguing possibility for organizations that want to use the best available database technology without the headaches of running and operating that technology.
Self-driving databases use cloud-based technology and machine learning to automate many of the routine tasks required to manage databases, such as tuning, security, backups, updates, and other routine management tasks. With these tedious tasks automated, database administrators are freed up to do more strategic work. The self-driving, self-securing, and self-repairing capabilities of self-driving databases are poised to revolutionize how companies manage and secure their data, enabling performance advantages, lower costs, and improved security.
The first autonomous database was announced in late 2017, and multiple independent industry analysts quickly recognized the technology and its potential impact on computing.
A Wikibon 2021 report (PDF) praised autonomous database technology, saying, “Oracle has by far the best Tier-1 Cloud Database Platform…Wikibon believes Oracle has the strongest Cloud Database Platform with Autonomous Database.”
And KuppingerCole’s 2021 Leadership Compass (PDF) said, "The Oracle Autonomous Database, which completely automates provisioning, management, tuning, and upgrade processes of database instances without any downtime, not just substantially increases security and compliance of sensitive data stored in Oracle Databases but makes a compelling argument for moving this data to the Oracle Cloud." Because Oracle Autonomous Database is built on the highly available and scalable architecture of Oracle Exadata, it’s possible to easily scale the database deployment as needs grow.