A database is a system for storing, managing, and retrieving data. It powers web applications by handling dynamic content, transactions, and user data. Databases work by electronically organizing information in a structured format and using a database management system (DBMS) to process queries and maintain data integrity. There are 6 main types of databases: relational, NoSQL, graph, search, time-series, and in-memory.
16 popular databases are MySQL, PostgreSQL, MongoDB, Redis, SQLite, Neo4j, Elasticsearch, DynamoDB, MariaDB, Microsoft SQL Server, Oracle Database, IBM DB2, Apache Cassandra, Apache CouchDB, OrientDB, and Firebird SQL. Each supports different workloads, from structured queries to distributed storage.
4 common uses of databases in websites and web apps are handling dynamic content, transactional support, user data management and efficient data retrieval. Web applications use databases to handle user accounts, product catalogs, shopping carts, and transactions.
Choose a relational database if your project requires structured data with relationships. Choose a non-relational (NoSQL) database if your website needs to handle large-scale unstructured or semi-structured data. A critical part of choosing a database is to verify its compatibility with your web host provider. Certain databases require specific server operating systems (OS) to function optimally. This means software compatibility is a critical consideration when choosing an appropriate web host for your project.
What Is a Database?
A database is a structured system for storing, managing, and retrieving data. Databases are typically electronic and store data in tables, documents, key-value pairs, or graphs, depending on the database type. They support applications by handling large amounts of data in a way that ensures consistency and enables quick searches.
Businesses, websites, and software use databases to store customer information, transaction records, content, and other critical data. Examples of databases include online shopping platforms storing product information and customer data and social media platforms storing user profiles and posts.
How Does a Database Work?
A database works by storing its data in an organized structure and allowing users or applications to retrieve, modify, and manage it. Databases are typically stored electronically and utilize a database management system (DBMS). The DBMS is software that handles database queries, enforces rules, and ensures data integrity. When a user requests information, the DBMS processes the query, retrieves the relevant data, and returns it in a structured format.
Databases use indexing, caching, and transaction management to optimize performance and maintain accuracy. Indexing creates data structures like B-trees to speed up searches by reducing scanned data. Caching stores frequently accessed data in memory to cut retrieval times and ease database load. Transaction management prevents partial updates and maintains data integrity.
What Are the Different Types of Databases?
Different types of databases refer to the variations of models designed to store, manage, and retrieve data. There are 6 types of databases:
- Relational database
- NoSQL database
- Graph database
- Search database
- Time-series database
- In-memory database
1. Relational Database
A relational database, also known as an SQL database, stores data in structured tables with predefined schemas. It uses structured query language (SQL) to manage and retrieve data. Relationships between tables help maintain data integrity and prevent duplication. Relational databases support transactions and ensure their accuracy. They are widely used in enterprise applications, banking systems, and content management platforms.
2. NoSQL Database
A NoSQL database, also known as a non-relational database, stores unstructured or semi-structured data in a flexible format. It includes document, key-value, column-family, and graph databases, each optimized for different workloads. NoSQL databases scale easily and handle large volumes of data, ideal for real-time applications, big data processing, and cloud-based services.
3. Graph Database
A graph database stores data as nodes and edges, and represents entities and their relationships. This structure allows for fast and efficient traversal, which makes graph databases ideal for social networks, fraud detection, recommendation systems, and network analysis. They’re different from relational databases as they’re able to quickly query complex connections without relying on joins.
4. Search Database
A search database is designed to store and retrieve text-based data efficiently. It uses indexing and full-text search capabilities to provide fast, relevant results for large datasets. Search databases are commonly used in search engines, eCommerce platforms, and customer support systems to enable keyword searches and real-time filtering.
5. Time-Series Database
A time-series database is optimized for storing and analyzing time-stamped data. It efficiently handles data with time-based patterns, such as IoT (Internet of Things) sensor readings, stock prices, and server logs. These databases support fast queries for trend analysis, forecasting, and anomaly detection, which make them essential for monitoring applications and real-time analytics.
6. In-Memory Database
An in-memory database stores data in RAM instead of disk storage, which enables ultra-fast read and write operations. It reduces latency and improves performance for applications requiring real-time processing, such as caching, gaming, financial transactions, and analytics. In-memory databases often include persistence options to prevent data loss since data is stored in volatile memory.
What Are the Popular Databases?
Popular databases refer to widely adopted database systems known for their reliability, scalability, and performance across various applications. There are 16 popular databases:
- MySQL
- PostgreSQL
- MongoDB
- Redis
- SQLite
- Neo4j
- Elasticsearch
- DynamoDB
- MariaDB
- Microsoft SQL Server
- Oracle Database
- IBM DB2
- Apache Cassandra
- Apache CouchDB
- OrientDB
- Firebird SQL
1. MySQL
MySQL is an open-source relational database that uses structured tables and Structured Query Language (SQL) to manage data. It supports ACID (Atomicity, Consistency, Isolation, and Durability) transactions, indexing, and replication. MySQL is known for its broad compatibility, ease of use, and active community support. It’s widely implemented in web applications, content management systems, and eCommerce platforms.
2. PostgreSQL
PostgreSQL is an advanced open-source relational database that prioritizes extensibility and data integrity. It offers ACID compliance, full-text search, and support for JavaScript Object Notation (JSON) data. PostgreSQL is widely adopted for enterprise applications, complex analytics, and data warehousing.
3. MongoDB
MongoDB is a NoSQL document database that stores data in flexible, JSON-like documents. It supports horizontal scaling, automatic sharding, and indexing. It’s ideal for handling large volumes of unstructured or semi-structured data in modern web applications and big data processing.
4. Redis
Redis is an in-memory key-value database designed for fast data retrieval with minimal latency. It supports data structures such as strings, lists, and hashes, along with persistence options for durability. Redis is commonly used for caching, real-time analytics, session storage, and message brokering.
5. SQLite
SQLite is a self-contained relational database that operates without a dedicated server. It stores data in a single file and is capable of supporting SQL queries and ACID transactions despite its small footprint. SQLite is widely integrated into embedded systems, mobile applications, and lightweight web applications.
6. Neo4j
Neo4j is a graph database that represents data as nodes and relationships instead of tables. It is optimized for querying complex relationships efficiently using its Cypher query language. Neo4j is suitable for social networks, fraud detection, and recommendation engines.
7. Elasticsearch
Elasticsearch is a distributed search database designed for full-text search, log analytics, and data indexing. It uses an inverted index structure to enable fast queries over large datasets. Elasticsearch is frequently applied in search engines, log analytics, and monitoring systems.
8. DynamoDB
DynamoDB is a fully managed NoSQL key-value and document database developed by Amazon Web Services (AWS). It automatically scales to handle high workloads while maintaining low-latency performance. DynamoDB is widely used in high-traffic applications, Internet of Things (IoT) ecosystems, and real-time analytics.
9. MariaDB
MariaDB is a MySQL-compatible relational database that enhances performance, security, and scalability. It offers additional storage engines and clustering support while maintaining MySQL compatibility. MariaDB is recommended for enterprise and cloud applications.
10. Microsoft SQL Server
Microsoft SQL Server (MSSQL) is a commercial relational database designed for Windows-based applications. It offers ACID-compliant transactions, enterprise-grade security, and built-in analytics. MSSQL integrates seamlessly with .NET applications and is commonly used in corporate environments.
11. Oracle Database
Oracle Database is a relational database designed for large-scale enterprise applications that require high availability, security, and multi-model data support. It offers advanced transaction management, partitioning, and in-memory processing for performance optimization. Oracle Database is commonly deployed in banking, finance, healthcare, and cloud-based enterprise systems.
12. IBM DB2
IBM DB2 is an enterprise relational database optimized for high-performance transaction processing, analytics, and artificial intelligence (AI)-driven applications. It supports structured and unstructured data, multi-platform deployments, and advanced security features. IBM DB2 is a key component in financial institutions, large-scale data warehousing, and government databases.
13. Apache Cassandra
Apache Cassandra is a NoSQL column-family database designed for distributed, high-availability environments. It provides fault tolerance, linear scalability, and decentralized architecture. Cassandra is a core technology in large-scale applications such as social media, IoT networks, and real-time data processing.
14. Apache CouchDB
Apache CouchDB is a NoSQL document database that uses a schema-free JSON format. It supports multi-version concurrency control and distributed replication, which enables seamless synchronization between devices. CouchDB is particularly effective for offline-first applications and decentralized data storage.
15. OrientDB
OrientDB is a multi-model database that integrates graph, document, object, and key-value storage within a single system. It efficiently processes complex relationship queries and distributed data. OrientDB is commonly used in fraud detection, knowledge graph applications, and high-performance analytics.
16. Firebird SQL
Firebird SQL is an open-source relational database that features ACID compliance, a multi-generational architecture, and cross-platform support. It is lightweight yet capable of handling complex transactional workloads. Firebird SQL is suitable for embedded systems, business applications, and enterprise solutions.
What Are Databases Used For?
Databases are used for 4 key purposes in web apps and websites. The first is managing dynamic content. Dynamic content refers to information that updates automatically based on user interactions or system changes. Websites with dynamic content rely on databases to store and update information such as blog posts, product listings, and user-generated content.
The second purpose is online transactional support, including payments, order placements, and financial records. They prevent duplicate payments, incomplete orders, and data loss by ensuring that each transaction is processed fully or not at all.
The third is user data management. Websites and applications store user profiles, login credentials, and preferences in databases. This enables personalized experiences like saved settings, recommendation systems, and secure authentication.
The fourth is efficient data retrieval. Databases optimize search and query execution to allow users to quickly find relevant information. This supports reporting, analytics, and filtering by structuring data for fast and accurate retrieval.
How Are Databases Used in Web Applications?
Databases are used in web applications to store, manage, and retrieve critical data, thus enabling smooth operations. An example web application is an online store, where a database performs 4 key functions.
First, the database stores user account information, including login credentials, and order history. This enables customers to sign in, track past purchases, and receive personalized recommendations. Second, it manages product data such as descriptions, prices, categories, and stock levels. This ensures that the product catalog automatically updates as inventory changes. Third, it supports shopping cart functionality and lets users resume shopping even after leaving the website. Fourth, it processes orders and payment by recording transaction details, shipping addresses, and payment confirmations.
What Database Should I Use for My Website?
You should use a relational database like MySQL, PostgreSQL, or Microsoft SQL Server if your website requires structured data with relationships. This includes eCommerce stores, content management systems (CMS), or business applications.
You should use a non-relational (NoSQL) database like MongoDB, DynamoDB, or Apache Cassandra if your website needs to handle large-scale unstructured or semi-structured data, such as real-time analytics, social media platforms, or Internet of Things (IoT) applications.
When you have selected a suitable database, ensure it is supported by your website’s web hosting provider. Web hosting refers to the service that stores your website files and databases and makes it accessible online. The best database hosting providers offer optimized server environments and full support for a range of databases, like MySQL, PostgreSQL, and MongoDB.
How Do I Know if a Web Host Supports a Certain Database?
Determine if a web host supports a certain database by checking its hosting plan details, reviewing its documentation, or contacting customer support. Most shared hosting providers list supported databases on their feature pages, while cloud hosts specify compatible database services. Verifying database compatibility is a critical step in choosing a web host plan that meets your project requirements. Database support depends not only on the host’s features but also on its server operating system (OS).
How Is Database Choice Affected by the Server OS of My Hosting?
Database choice is affected by the server OS of your hosting because certain databases are designed to work best with specific OS environments. The server OS refers to software that manages server resources and runs applications. The 2 main server OS are Linux and Windows.
Linux hosting is optimized for open-source databases like MySQL, PostgreSQL, and MariaDB. Windows hosting is necessary for databases like Microsoft SQL Server (MSSQL) and Microsoft Access. Choosing a database that is incompatible with your web host’s server OS causes performance issues and limits available management tools.