What is a Database?

A database is an organized collection of information that can be stored, managed, searched, and updated. In a business setting, a database might store customer names, addresses, purchase histories, support tickets, and other records that a company needs to access over time. Oracle defines a database as an organized collection of information used to store and retrieve related data for applications.

Many databases organize information in tables made up of rows and columns. Unlike a spreadsheet, which is often used for smaller or less complex datasets, a database is designed to manage larger amounts of structured information, support queries, and allow multiple users or applications to work with the data. For example, a sales team, customer service team, and billing system might all rely on the same customer database.

A database management system, or DBMS, is the software used to create, update, organize, secure, and retrieve information from a database. Common examples include Oracle Database, Microsoft SQL Server, MySQL, and PostgreSQL. Together, a database and its DBMS help organizations keep data organized, searchable, and usable for reporting, operations, analytics, and decision-making.

Who Uses a Database?

Businesses can use databases to better organize and use their data, which has a number of benefits. Databases can help businesses assess performance and make informed decisions. A business might use its database to build better relationships with customers, implement more effective marketing, assess the performance of new products or offers, and much more.

Databases fulfill many roles, some of which may benefit from basic or even advanced database skills.

For instance, marketing professionals may use databases to oversee marketing campaigns, nurses might use electronic healthcare record databases to manage patient data, and customer service representatives may access and input customer data through databases.

Prospective students interested in these roles may also want to explore related career paths, such as data engineer and data architect, which involve designing and building the broader data infrastructure that supports databases.

Different Database Types

There are many types of databases, and they all work in different ways. The best type of database for a business will depend on its focus and how it stores and uses data. Additionally, as some businesses grow, they may need to use multiple types of databases for different applications to simplify maintenance and debugging.

Many variables come into play when a business chooses the right database(s). Some common types include:

• Relational databases.
• Distributed databases.
• Object-oriented databases.
• Open-source databases.
• Cloud databases.
• Vector databases.

Relational Database

Relational databases store information in tables with rows and columns. These databases allow multiple users to access data simultaneously, support data recovery after a failure, and operate across multiple platforms. MySQL, Oracle, Microsoft SQL Server, and PostgreSQL are all common examples of relational databases. Relational databases remain widely used by organizations of all sizes, from startups to large enterprises, and serve as the foundation for SQL, the query language that underpins much of modern data analysis.

Distributed Database

While many databases consist of a centralized collection of data, distributed databases take a different approach. These databases consist of two or more files stored in different locations — sometimes on completely different networks. Users can still access and edit data, but the files must be synchronized. This type of database offers a major advantage in resilience: if one site fails, data can still be retrieved from another. Examples of distributed databases include Apache Cassandra, Amazon DynamoDB, and Google Spanner.

Object-Oriented Database

An object-oriented database stores data as objects and is based on a type of object-oriented programming like C++, Java, Python or JavaScript. Object databases offer many benefits, including the ability to handle complex data, quick access to that data and more efficient coding than other database types. Common object-oriented databases include Cache, ConceptBase, ObjectDB Object Database and Versant Object Database. These types of databases are often used in situations where fast results and calculations are necessary, such as in telecommunications, molecular science and 3D architecture and engineering.

Open-Source Databases

Open-source databases are made available to the public, often at no cost, allowing businesses to access and modify the source code to customize them. Many open-source databases offer robust data security, collaborative features, and cross-platform support. The flexibility and customization options make open-source databases practical for a wide array of businesses. Popular examples include PostgreSQL, MySQL, and MongoDB.

Cloud Databases

Cloud databases are hosted on a cloud computing platform. That cloud platform can be a public, private or hybrid platform. Cloud databases depend less on hardware, and as a result tend to be much easier to scale. Because businesses don’t need to focus on expensive upgrades, cloud databases are often more economical. They may also offer enhanced security. Common cloud databases include Oracle, Amazon Web Services, Microsoft Azure and Google Cloud Platform.

Vector Databases

A relatively new and rapidly growing database type, vector databases are purpose-built to store and query high-dimensional data representations called embeddings, numerical arrays that capture the semantic meaning of content like text, images, and audio. They are a foundational component of modern AI applications, enabling fast similarity search across large volumes of unstructured data. Vector databases power use cases such as AI chatbots, recommendation systems, and retrieval-augmented generation (RAG), a technique that connects large language models (LLMs) to proprietary data sources. Leading platforms include Pinecone, Weaviate, Milvus, and Chroma, as well as vector search capabilities now integrated into major cloud databases, including Google AlloyDB, AWS OpenSearch, and Azure SQL. According to IBM, vector database adoption grew 377 percent year over year as of 2025, reflecting its central role in the generative AI era.