Top 15 Databases for Web Apps to Use in 2025

 

When building a web application, selecting the right database is one of the most critical decisions you’ll make. The database you choose will directly impact how your app performs, scales, and handles data. In 2025, the database landscape is more diverse than ever, offering a mix of relational and NoSQL databases, each with its own strengths and ideal use cases. Whether you’re building a small blog or a large-scale enterprise application, there’s a database out there that’s perfect for your needs. 

In this blog, we’ll explore the top 15 databases for web apps in 2025. 

 

Explore the 2025 database landscape with an overview of top databases: 

 

1. MySQL 

MySQL has been a cornerstone of web development for decades, and its popularity shows no signs of waning in 2025. As an open-source relational database, MySQL is known for its speed, reliability, and ease of use. It’s a great choice for applications that rely on structured data, such as blogs, e-commerce platforms, and content management systems (CMS). MySQL’s ACID compliance ensures data integrity and reliability, even in complex systems. Its wide community support makes it easy to find resources and solutions, and while it’s ideal for small to medium-sized applications, MySQL can also handle larger projects with proper optimization. For developers looking for a balance of performance and ease of use, MySQL remains a top choice. 

One of the key reasons MySQL continues to thrive is its simplicity. Setting up a MySQL database is straightforward, and its compatibility with a wide range of programming languages and frameworks makes it a versatile option. Additionally, MySQL’s replication features allow for high availability and load balancing, which are essential for growing applications. Whether you’re building a personal blog or a mid-sized e-commerce platform, MySQL offers the reliability and performance you need. 

 

2. PostgreSQL 

PostgreSQL is often referred to as the most advanced open-source relational database. It’s designed for developers who need to handle complex queries and large datasets. Unlike MySQL, PostgreSQL supports advanced data types like JSON, arrays, and even geospatial data, making it a versatile choice for modern applications. Its ACID compliance ensures data consistency and reliability, and its robust support for concurrency makes it suitable for highly transactional systems. PostgreSQL is particularly well-suited for large-scale enterprise applications, data-heavy platforms, and systems requiring advanced data handling. If your application demands flexibility and scalability, PostgreSQL is a strong contender. 

PostgreSQL’s extensibility is another standout feature. Developers can add custom functions, data types, and even programming languages to tailor the database to their specific needs. This makes PostgreSQL a favorite for applications that require unique or specialized data handling. Additionally, PostgreSQL’s support for advanced indexing techniques, such as partial indexes and expression indexes, allows for faster query performance, even with large datasets. For businesses dealing with sensitive data, PostgreSQL’s robust security features, including role-based access control and data encryption, provide an added layer of protection. 

 

3. MongoDB 

MongoDB is a leading NoSQL database that has gained immense popularity for its flexibility and scalability. Unlike traditional relational databases, MongoDB uses a document-based model, storing data in JSON-like formats called BSON. This makes it ideal for applications with evolving data schemas. MongoDB shines when it comes to scalability, supporting horizontal scaling through sharding, which allows it to handle large volumes of data and traffic with ease. It’s also a great choice for applications that require real-time processing and high availability. With built-in replication, your data remains accessible even in the event of server failures. MongoDB is perfect for real-time applications, social media platforms, and content management systems with diverse data types. 
 

One of MongoDB’s standout features is its ability to handle unstructured or semi-structured data. This flexibility is particularly useful for applications where the data schema may change over time, such as in agile development environments. MongoDB’s aggregation framework also allows for complex data transformations and analysis, making it a powerful tool for data-driven applications. Additionally, MongoDB Atlas, the database’s cloud offering, provides a fully managed solution with automatic scaling, backups, and security features, making it an attractive option for businesses looking to reduce operational overhead. 

 

4. SQLite 

SQLite is a lightweight, serverless relational database that’s perfect for smaller applications or environments with limited resources. Unlike other databases, SQLite stores all its data in a single file, making it highly portable and easy to set up. It’s a zero-configuration database, meaning it requires little setup and is ideal for mobile apps, embedded systems, and prototyping. SQLite’s simplicity and speed make it a favorite for developers who need quick access to local storage without the overhead of a full-fledged server-based database. If you’re building a mobile app or a small-scale application, SQLite is an excellent choice. 

SQLite’s self-containing nature makes it incredibly easy to deploy. Since it doesn’t require a separate server process, it can be integrated directly into an application, reducing complexity and resource usage. This makes SQLite a popular choice for IoT devices, where resources are often limited. Additionally, SQLite’s transactional support ensures data integrity, even in environments where power failures or crashes may occur. For developers looking for a simple, fast, and reliable database solution, SQLite is a top contender. 

 

5. MariaDB 

MariaDB is a fork of MySQL, created by the original developers of MySQL. It’s fully compatible with MySQL but offers additional features, better performance, and enhanced security. MariaDB is an excellent choice for developers who want more advanced capabilities without switching to a completely new system. It supports dynamic columns, improved indexing, and multi-source replication, making it a strong choice for high-traffic websites and e-commerce platforms. MariaDB’s ability to scale better than MySQL makes it ideal for applications that require complex queries and optimization. If you’re looking for a cost-effective, open-source database with advanced features, MariaDB is a great option. 
 

MariaDB’s focus on performance and security sets it apart from its predecessor. Features like parallel replication and query optimization ensure that MariaDB can handle high workloads efficiently. Additionally, MariaDB’s support for NoSQL interfaces, such as JSON and Cassandra storage engines, allows developers to combine the best of both relational and NoSQL worlds. For businesses that need a reliable, high-performance database with advanced features, MariaDB is a compelling choice. 

 

6. Redis 

Redis is an in-memory key-value store that’s widely used for caching and real-time data processing. Its ability to deliver sub-millisecond response times makes it a favorite for applications that require lightning-fast data retrieval. Redis stores data directly in RAM, leading to faster read and write operations. It supports a wide range of data structures, including strings, lists, sets, and hashes, making it highly versatile for different use cases. Redis is particularly well-suited for managing real-time data, such as user sessions, message queues, and leaderboards. If your application requires low-latency data access, Redis is an excellent choice. 
 

Redis’s in-memory architecture makes it ideal for use cases where speed is critical. For example, in e-commerce platforms, Redis can be used to cache product catalogs, reducing load times and improving the user experience. Additionally, Redis’s support for pub/sub messaging makes it a great choice for real-time applications like chat platforms and live notifications. With features like data persistence and replication, Redis ensures that your data remains safe and accessible, even in high-traffic environments. 

 

7. Cassandra 

Apache Cassandra is a distributed NoSQL database designed to handle massive amounts of data across multiple servers. It’s known for its high availability and fault tolerance, making it a great choice for applications that can’t afford downtime. Cassandra’s distributed architecture allows it to scale horizontally, meaning you can add more nodes as your application grows. It also supports eventual consistency, which ensures data remains available across multiple regions or data centers. Cassandra is ideal for big data applications, real-time analytics, and systems requiring high availability and fault tolerance. 
 

Cassandra’s ability to handle large volumes of data with no single point of failure makes it a favorite for mission-critical applications. For example, in the financial industry, Cassandra is often used to process and store transaction data in real time. Its decentralized architecture ensures that even if one node fails, the system continues to operate without interruption. Additionally, Cassandra’s support for tunable consistency allows developers to balance performance and data accuracy based on their specific needs. If you’re building an application that requires high scalability and reliability, Cassandra is a strong contender. 

 

8. ElasticSearch 

ElasticSearch is a powerful search and analytics engine that’s perfect for applications requiring real-time search capabilities. It’s built on Apache Lucene and can handle both structured and unstructured data with ease. ElasticSearch’s real power lies in its ability to search through huge datasets in milliseconds. It’s highly optimized for real-time searches and is often used to power search functionality in websites, applications, and enterprise systems. ElasticSearch integrates well with other systems and can handle unstructured data, making it ideal for logs, social media data, and e-commerce product catalogs. 
 

ElasticSearch’s distributed nature allows it to scale horizontally, making it suitable for applications with large and growing datasets. Its support for full-text search, geospatial search, and complex aggregations makes it a versatile tool for a wide range of use cases. Additionally, ElasticSearch’s integration with Kibana provides powerful visualization capabilities, allowing businesses to gain insights from their data in real time. Whether you’re building a search engine or a log analysis platform, ElasticSearch is a robust and scalable solution. 

 

9. Firebase Realtime Database 

Firebase Realtime Database, part of Google’s Firebase platform, is a NoSQL database designed for real-time data synchronization. It’s perfect for applications that require instant updates, such as chat apps or collaborative tools. Firebase handles all the backend infrastructure, allowing developers to focus on building the app without worrying about server maintenance or data synchronization issues. Since Firebase supports serverless computing, developers don’t need to manage database instances or servers manually. If you’re building a real-time app or a mobile application that requires live data updates, Firebase is an excellent choice. 

Firebase’s real-time capabilities make it ideal for collaborative applications, such as project management tools or multiplayer games. Its offline support ensures that users can continue to interact with the app even when they’re not connected to the internet, with changes syncing automatically once connectivity is restored. Additionally, Firebase’s integration with other Google Cloud services, such as Cloud Functions and Cloud Storage, provides a comprehensive backend solution for modern applications. For developers looking to build real-time, collaborative apps quickly and efficiently, Firebase is a top choice. 

 

10. CockroachDB 

CockroachDB is a distributed SQL database that combines scalability with strong consistency. It’s designed to handle global applications, ensuring high availability and reliability across multiple regions. CockroachDB supports ACID transactions and is built to scale horizontally without adding complexity. It’s ideal for transactional workloads that require high reliability, such as financial applications or e-commerce platforms. If your application needs to operate seamlessly across multiple regions, CockroachDB is a strong contender. 
 

CockroachDB’s architecture is inspired by Google’s Spanner, providing global consistency without sacrificing performance. Its ability to automatically replicate data across multiple nodes ensures high availability, even in the event of hardware failures. Additionally, CockroachDB’s support for SQL makes it easy for developers to transition from traditional relational databases. For businesses that need a scalable, globally distributed database with strong consistency guarantees, CockroachDB is an excellent option. 

 

11. Oracle Database 

Oracle Database is a powerhouse in the enterprise world, offering robust features for large-scale applications. It’s known for its reliability, security, and advanced data management capabilities. Oracle Database includes built-in encryption, access controls, and comprehensive tools for analytics and machine learning. It’s optimized for large datasets and is a great choice for financial and healthcare systems that require advanced security and compliance. If you’re building an enterprise-level application, Oracle Database is a reliable option. 

Oracle’s Multitenant architecture allows multiple databases to be consolidated into a single container, reducing overhead and simplifying management. Its support for in-memory processing and advanced compression techniques ensures high performance, even with large datasets. Additionally, Oracle’s Autonomous Database offering provides a fully managed solution with automated backups, patching, and scaling, making it an attractive option for businesses looking to reduce operational complexity. For enterprises that need a robust, secure, and scalable database, Oracle is a top choice. 

 

12. Microsoft SQL Server 

Microsoft SQL Server is a reliable relational database that integrates seamlessly with other Microsoft products. It’s a great choice for businesses already using the Microsoft ecosystem. SQL Server offers advanced analytics, built-in support for machine learning and AI, and seamless integration with Azure for cloud-based applications. It’s scalable and handles large datasets with ease, making it ideal for enterprise applications and cloud-based systems. 
 

SQL Server’s support for in-memory OLTP and columnstore indexes ensures high performance for transactional and analytical workloads. Its integration with Power BI provides powerful data visualization capabilities, allowing businesses to gain insights from their data quickly. Additionally, SQL Server’s Always On availability groups ensure high availability and disaster recovery, making it a reliable choice for mission-critical applications. For businesses invested in the Microsoft ecosystem, SQL Server is a robust and versatile database solution. 

 

13. DynamoDB 

Amazon DynamoDB is a fully managed NoSQL database designed for high performance and scalability. It’s a great choice for applications that need to handle large volumes of data with low latency. DynamoDB’s serverless architecture eliminates the need to manage infrastructure, and its automatic scaling ensures it can handle traffic spikes effortlessly. If you’re building a high-traffic web app or a real-time application, DynamoDB is an excellent option. 
 

DynamoDB’s support for ACID transactions and global tables makes it ideal for applications that require strong consistency and global scalability. Its integration with AWS services, such as Lambda and S3, provides a comprehensive backend solution for modern applications. Additionally, DynamoDB’s pay-per-use pricing model ensures cost efficiency, making it an attractive option for startups and businesses with variable workloads. For developers looking for a scalable, high-performance NoSQL database, DynamoDB is a top choice. 

 

14. Neo4j 

Neo4j is a graph database designed for applications that require complex relationship mapping. It’s perfect for social networks, recommendation engines, and fraud detection systems. Neo4j’s graph-based model allows it to handle relationship-heavy data efficiently, and its high performance makes it ideal for complex queries. If your application relies on analyzing relationships between data points, Neo4j is a great choice. 

Neo4j’s Cypher query language provides a powerful and intuitive way to query graph data, making it easy for developers to work with complex relationships. Its support for ACID transactions ensures data integrity, even in high-concurrency environments. Additionally, Neo4j’s graph algorithms and machine learning integrations provide advanced analytics capabilities, making it a versatile tool for data-driven applications. For businesses that need to analyze and visualize complex relationships, Neo4j is a robust and scalable solution. 

 

15. InfluxDB 

InfluxDB is a time-series database designed for applications that require real-time analytics and monitoring. It’s perfect for IoT, DevOps, and financial applications. InfluxDB is optimized for timestamped data and can handle large volumes of time-series data with ease. If you’re building an application that requires real-time analytics, InfluxDB is an excellent option. 
 
InfluxDB’s support for high-precision timestamps and downsampling ensures accurate and efficient storage of time-series data. Its integration with Telegraf and Grafana provides powerful data collection and visualization capabilities, making it easy to monitor and analyze real-time data. Additionally, InfluxDB’s support for Flux, a powerful scripting language, allows for complex data transformations and analysis. For businesses that need to process and analyze time-series data in real time, InfluxDB is a top choice. 

 

Conclusion 

Choosing the right database for your web application is a decision that can make or break your project. Whether you’re building a small blog or a large-scale enterprise system, the database you choose will play a crucial role in your app’s performance, scalability, and user experience. 
 

In 2025, the options are more diverse than ever, ranging from traditional relational databases like MySQL and PostgreSQL to NoSQL powerhouses like MongoDB and Cassandra. Each database has its own strengths and ideal use cases, so it’s important to carefully evaluate your needs before making a decision. 
 

At Intelegain Technologies, we specialize in helping businesses identify and implement the best database solutions for their web applications. Whether you’re building a small app or an enterprise-level system, we provide expert guidance and assistance in integrating the right database technology for your project. Reach out to us today to explore how we can help streamline your development process and ensure your app’s success.