Top 15 Best Databases for Web Applications to Use In 2025

Behind every web application, from your favorite entertainment streaming platform to a trip ticket booking website, a versatile and robust database is at play, ensuring a streamlined information flow. But today, in the year 2025, the role of databases in web applications has transcended beyond just being a unit for data storage and retrieving. With the advent of multi-cloud infrastructure, real-time analytics, AI-driven automation, etc., modern databases have transformed into dynamic entities that can adjust storage dynamically as per workload demands, predict failure, and even self-optimize, enlightening us about the evolving technology. 

The cloud database market is expected to reach nearly $56 Billion by this year, boosted by a shift towards AI-powered and serverless database management systems. 

In this detailed guide, we will explore how databases shape the scalability, security, and performance of web applications and the top features, pros, and cons of the 15 databases to choose from in 2025. Dig in. 

Importance of databases in web applications 

Here's how databases empower web applications: 

Increases speed, reduced latency 

Slow databases mean slow web applications, which are irrelevant to users in today's era of 5G speed. A study by Google found that even a 1-second delay in the page's load time can reduce the conversion rate by 7%, underlining the urgent need for speed optimization. 

Optimized databases ensure that the queries are executed in milliseconds. 

Example: Twitter once switched to a high-performance combination of Redis Caching and MySQL so that it could optimally handle 6,000 tweets each second. This transition also reduced its query latency by 40%. 

Future proof your web apps with scalability and security 

Let’s explore the scalability and security factors of databases in web  applications 

Scalability 

With the growth of your business, the volumes of data generated grow too. A robust database can handle billions of requests without any downtime. There are two types of scalabilities: 

1. Horizontal – Which distributes the data across multiple servers. Found commonly in NoSQL servers.
2. Vertical – This upgrades a single server for more power. Found commonly in SQL servers. 

Intuit, popular for its financial products like QuickBooks, used MicrosoftSQL server, which scaled vertically for effectively handling massive volumes of structured financial data. 

Security 

In 2024, a sudden security data breach cost a company nearly $4.45 million, and in the coming years, it will definitely rise. With new innovations and upgrades, data breaches are common as well. A secure database, in this case, will protect your web applications from: 

1. Unauthorized access
2. SQL injection attacks
3. Ransomware threats 

Facilitates compliance and data integrity 

Sectors where data plays a critical role, like Government, finance, healthcare, etc., adhere to stringent compliance standards, and maintaining flawless data integrity is paramount. Generally, robust ACID transactions are employed to guarantee that every data operation is consistent and accurate. 

Frameworks like HIPAA and GDPR also require strict security measures to ensure the protection of sensitive information. 

Did you know that nearly 75% of companies operating in regulated industries have succeeded in adopting end-to-end encryption for the databases they use? It's a decisive strategy for safeguarding data integrity and preventing compliance breaches. 

Types of Databases for web applications 

Databases are considered to be the spine of web applications. Their essential functions are to provide seamless data storage, retrieval, and management. When you choose the proper database for your enterprise, you are implementing easy maintainability, dynamic scalability, and optimal performance. In a broad classification, databases fall under two categories, which are SQL (relational) and NoSQL (non-relational), and based on their application needs, each of these offers advantages. Let's have a detailed look at their critical aspects: 

SQL vs. NoSQL: crucial differences 

SQL and NoSQL databases meet different enterprise processing and data storage needs. Take a look at their functional and structural differences: 

• Difference based on data structure: SQL databases leverage structured tables with predefined schemas. NoSQL databases facilitate flexible schema-less data models.
• Differences based on scalability: SQL databases, in general, scale vertically, adding more power to a singular server. NoSQL databases scale horizontally, distributing data across multiple servers.
• Differences based on query language: SQL databases leverage structured query language for data manipulation. NoSQL databases use various models of data access, such as graph-based approaches, column family stores, and key-value stores.
• Differences based on consistency vs. availability: SQL databases emphasize consistency by complying with ACID (Atomicity, Consistency, Isolation, and Durability). NoSQL databases, in favor of high partition difference tolerance and availability, often sacrifice stringent consistency factors. 
   

An overview of SQL (relational) databases 

SQL databases are used widely for the applications that require strong consistency and proper structurization for data storage. These databases adhere to the relational model, where all data is stored with predefined relationships and stored in tables. Details below: 

• Structured data storage 

SQL databases the data into columns and rows and enforces relationships through foreign and primary keys. This approach ensures easy querying and data integrity. 

• ACID compliance 

SQL databases are compliant to ACID properties - Atomicity, Consistency, Isolation, and Durability. These factors make the databases reliable for the applications who require consistency in transaction. The properties also ensure that the data operations are accurately processed by maintaining integrity even when there's a failure. 

Some notable SQL databases are Oracle, Microsoft SQL Server, PostgreSQL, and MySQL. 

An overview of NoSQL (non-relational) databases 

NoSQL databases provide great flexibility in handling structured, semi-structured, and highly unstructured data. These databases are great for applications that need real-time processing, distributed architectures, and high scalability. Details below: 

Flexible schema 

NoSQL databases never enforce a strict schema. This flexibility enables developers to modify and store data without any predefined structure, making them ideal for dynamic applications like social media platforms, IoT data storage, and CMS. 

High scalability 

NoSQL databases are ideal for distributed architectures, which makes them scalable. They use horizontal scaling, where the data is divided across various nodes, ensuring the effective and efficient handling of high-user traffic and large datasets. 

Some notable NoSQL databases are DynamoDB, Redis, and Cassandra. 

It is reported that by 2025 end, 80% of startups will be switching to hybrid SQL or NoSQL, balancing flexibility and scalability. 

What are the key factors for choosing a database? 

Picking the most suitable database is not only about going with the most popular one in the market – you have to choose the one that meets your needs by striking the right balance between cost, scalability, security, and speed. Whether you are building a high-traffic enterprise solution or a small-scale SaaS solution, the database that you choose will have a direct impact on the performance of your app as well as its long-term relevance and functionality. Here are the factors that you must consider: 

Performance and scalability 

Web applications must handle the rising user data loads alongside ensuring a quick execution of queries with low latency. Whether you are executing real-time analytics or many concurrent users, seamless performance is always the key. Make sure the database of your choice provides the following: 

• Vertical and horizontal scaling for accommodating dynamic growth
• Optimal load balancing for efficient traffic distribution
• Automated indexing for rapid execution 

The most ideal databases: MongoDB, Cassandra for high-speed distributed applications; MySQL and PostgreSQL for transactional systems. 

Data protection and security 

With the escalating cyber threats around us, data security is never something to be compromised as a factor. Make sure the database of your choice provides the following: 

1. Compliance with SOC 2, HIPAA, and GDPR for regulated industries
2. RBAC or role-based access for limiting exposure
3. End-to-end encryption for protecting sensitive data
4. MFA or multi-factor authentication for securing access 

Economical 

Costs of databases vary based on factors like computing power, storage, and licensing. It is vital that you choose the right price model like serverless (pay-per-use) or opensource for proper cost management. Choose from: 

• Enterprise solutions like Microsoft SQL server that offer advanced features. But they are heavy on the cost side
• Open-source databases like MySQL and PostgreSQL reduce licensing fees
• Serverless solutions like Firebase Firestore or Amazon Aurora are pay-per-use 

Easy to integrate 

Databases must seamlessly integrate with the web application's APIs, third-party services, and existing tech stack. The cross-platform ability assures flexibility for upgrades in the future. Make sure that the database of your choice: 

• Is compatible with CI/CD pipelines for automatic deployments
• Extends support for various programming languages like Java, Node.js, and Python
• GraphQL and REST APIs for efficiently retrieving data 

On-premises hosting vs. cloud 

The options between on-premises and cloud-hosted databases depend on factors like maintenance costs, security, and scalability. Here are the major points of differences: 

1. On-premises databases like Microsoft SQL Server or Oracle provide greater security and control but require dedicated infrastructure and resources.
2. Cloud-based databases like Google Cloud Spanner or AWS RDS are scalable solutions that provide automated backups and need minimum maintenance costs. 

By evaluating these crucial factors, business owners like you will be able to choose future-proof databases that meet unique performance demands while ensuring compliance, security, and, of course, cost efficiency. 

The top 15 databases ruling the web app development market 

With the world of web applications undergoing a rapid transformation, databases that can handle AI-powered automation, real-time analytics, massive scalability, and high-speed transactions are in demand. Whether your enterprise needs a NoSQL database for high availability and flexibility or a relational database for data structurization, picking the proper database is crucial for future scalability, security, and performance. 

Explore the list of top 15 databases that empower modern web applications with a small glimpse at their unique aspects. 

1. MySQL – a robust system for web application  

As one of the most preferred relational databases, MySQL is popular for its user-friendliness, reliability, and speed. It's an open-source database that powers millions of applications for enterprises of different calibers—from startups to large-scale enterprises. It has ACID compliance and offers high-performance indexing and replication that efficiently handle complex queries. 

Notable features: 

• ACID compliant
• For distributed applications, it facilitates horizontal scaling
• The InnoDB storage engine allows indexing and rapid transactions 

Meta, previously known as Facebook, leverages MySQL to handle billions of user-interaction data daily and store back-end data. 

2. PostgreSQL – An advanced open-source database 

PostgreSQL is a feature-rich and powerful database developed for handling complex queries, high concurrency, and extensibility. It has strong data integrity mechanisms, full-text search, and JSONB support, which makes it the best choice for enterprises that need semi-structured and structured data processing. 

Notable features: 

• Stored procedures and custom data types for better processing
• Its JSONB support and full-text search enable handling diverse data types
• Multiversion Concurrency Control and MVCC ensure seamless transactions 

Reddit leverages PostgreSQL to process real-time discussions, comments, and millions of upvotes. 

3. Microsoft SQL Server – for enterprise-grade security and performance 

Microsoft SQL Server is a favorite among various enterprises for its seamless integration with Microsoft Azure, real-time analytics, top-tier security, etc. Its data encryptions, AI-based optimizations, and always-on availability ensure that mission-critical apps function with high uptime and high performance. 

Notable features: 

• For hybrid applications, it facilitates seamless cloud integration with Microsoft Azure
• For predictive analytics, it has in-built AI and ML models
• For enterprise-level security, it has transparent data encryption (TDE) 

Stack Overflow uses a Microsoft SQL server to ensure the fast query responses of millions of developers. 

4. Oracle Database – a gold standard database for large-scale apps 

Oracle is ideal for global enterprises, Government agencies, and financial institutions as it's a highly secure and enterprise-grade RDBMS. It comes with advanced security controls, self-repairing capabilities, automated indexing, etc., which makes it a preference for leading organizations due to its unmatched uptime and data consistency. 

Notable features: 

• RAC or real application clusters for high-availability deployments
• Favors multi-model support with Blockchain, Graph, JSON, NoSQL, SQL
• To minimize human intervention and downtime, it is based on autonomous database technology 

5. MariaDB – MySQL's opensource innovation 

MariaDB was developed as an alternative to MySQL. It supposedly offers better security features, storage engines, and performance and is, of course, fully compatible with MySQL. Its columnar storage, JSON support, and parallel queries make it well-optimized for analytical workloads and cloud applications. 

Notable features: 

• Enterprise-grade capabilities with open-source licensing
• Parallel processing for facilitating high-speed performance
• Super-fast analytical queries enabled by ColumnStore Engine 

Wikipedia switched to MariaDB to obtain efficient large-scale data. 

6. IBM Db2 – an AI-powered database for enterprises 

IBM Db2 is an AI-powered high-performance database that excels in hybrid cloud deployments, financial transactions, and real-time analytics. Its native AI-powered optimizations empower businesses to extract insights faster and more accurately while ensuring ACID-compliant, secure, and reliable transactions. 

Notable features: 

• In-memory computing for high-speed performance
• AI-powered query optimization for quick retrieval of data
• Supported by Kubernetes for hybrid multi-cloud deployment 

Bank of America potentially uses IBM Db2 for securing its financial transactions 

7. SQLite – an efficient, lightweight database 

SQLite is a serverless and self-contained database proactively used for small-scale web applications, IoT devices, and mobile apps. It is perfect for local storage in mobile platforms and browsers and needs zero configuration. 

Notable features: 

• Writes and reads at a quick pace with low consumption of resources
• Lightweight format with full compliance with ACID factors
• Serverless and embedded architecture that eliminates the need for configuration 

Apple iOS leverages SQLite as its default local database for secured storage of its app data. 

8. MongoDB – a popular NoSQL database 

MongoDB is a popular, document-oriented, and highly scalable NoSQL database that provides real-time analytics, automatic sharding, and flexible schema designs. It's great for applications that manage and handle JSON-based, unstructured data. 

Notable features: 

• It has a robust aggregation framework for real-time analytics
• Processes massive datasets with its built-in sharding and horizontal scaling
• Schema-less and flexible architecture for quick app development 

EBay uses MongoDB for processing and storing its vast product catalog data. 

9. Redis – developers' favorite to build blazing-fast apps 

Redis is an in-memory, non-relational database that is optimized for messaging queues, real-time applications, and high-speed caching. It has ultra-low latency and is perfect for AI-powered platforms and quick-loading web apps. 

Notable features: 

• Pub/Sub messaging support, crucial for real-time apps
• In-built persistence and replication options
• In-memory storage for data that enables sub-millisecond response times 

Twitter, now X, caches trending topics and timelines by using Redis. 

10. Cassandra – The Distributed Powerhouse for Big Data 

Apache Cassandra is a dependable, non-relational database that is developed for fault tolerance and high availability. It is designed to handle large data volumes across different nodes and is ideal for applications with low global scalability and low latency for writing and reading. 

Notable features: 

• Linear scalability for effortlessly handling petabytes of data
• Replication is automated across different data centers
• Peer-to-peer and masterless architecture that assures no point of failure 

Instagram heavily relies on Cassandra to store billions of user interactions and photos across a vast distributed network. 

11. DynamoDB – A full-managed NoSQL databased by AWS 

DynamoDB by Amazon is a key-value, serverless NoSQL database. It provides built-in security, automatic scaling, and speed performance. It is popular for developers building e-commerce platforms, IoT apps, and real-time gaming. 

Notable features: 

• For event-driven apps, DynamoDB can be integrated with AWS Lambda
• In-built security and encryption features
• On-demand capacity scaling for handling dynamic traffic 

AirBnB leverages DynamoDB to manage user preferences and billions of users' real-time bookings globally. 

12. Neo4j – a great graph database for complex data 

Neo4j is a graph database that is built for interconnected and complex data. It is ideal for applications like recommendation engines, fraud detection, and social networks as it stores relationships as first-class data – an unusual aspect of traditional databases. 

Notable features: 

• Compliant with ACID elements for maintaining transactional consistency
• Optimizes Cypher query language for traversing relationships
• Enables processing for highly connected data and native graph storage 

NASA leverages Neo4j to build its data mapping database and various other apps. 

13. OrientDB – a versatile multi-model database 

OrientDB is a multi-model, non-relational database that combines the power of key-value stores, objects, documents, and graphs. It is ideal for developing applications that require fast query execution and highly flexible data models. 

Notable features: 

• Super-fast performance with SQL-like queries and native indexing
• For large-scale applications, it provides distributed clustering
• Provides support for different data models under a single database 

14. Elasticsearch – a top choice for search analytics and logs 

Elastic search is an analytics and real-time search engine developed for handling structured and unstructured data, text-based queries, and log data. It is used widely in real-time monitoring tools and search-driven applications. 

Notable features: 

• Easily integrable with Logstash and Kibana for robust analytics
• NLP capabilities with full-text search
• Distributed engine powering massive datasets 

Wikipedia leverages Elasticsearch to power its instant result deliverance and seamless search functionalities for its millions of users. 

15. FirebirdSQL – The super-performing opensource DBMS 

As a lightweight relational database, FirebirdSQL is popular for its cross-platform support, minimal maintenance, and high-speed performance. It is used mainly for building industrial applications that need stable and high throughput databases, medical and ERP systems, etc. 

Notable features: 

• Server-based and embedded models that facilitate flexible deployment
• MGA or multi-generational architecture for seamless concurrency
• High-speed processing for transactions facilitated by low system footprint 

Frontrange Solutions USA leverages FirebirdSQL at the back end for the Goldmine software suite, which includes business systems, service management systems, and CRM. 

Best practices for database security and performance 

A secured and well-optimized database creates the very backbone of any high-performing web application. Poorly performing databases lead to slowed load times and gradually become vulnerable when exposed to critical breaches in data. Here's how you can maximize your database efficiency and protect your company's sensitive information: 

Always optimize queries for rapid loading 

Slow queries in the database significantly impact the server performance and user experience. Efficient query optimization ensures the applications function smoothly, especially under heavy loads. Here's what you can do: 

• Index the critical columns to speed up the search operations by decreasing the full table scans.
• Query caching regularly will minimize the workload in the database
• Partition large tables for improving writing and reading efficiency through logical data distribution
• Leverage connection pooling to reduce overhead through efficient management of multiple user connections
• Optimize subqueries and joins to ensure minimal data retrieval overhead 

The best tools here are MySQL Optimizer, Aggregation Framework, MongoDB, and PostgreSQL EXPLAIN ANALYZE. 

Protection from cyber threats and SQL injections 

With the rising instances of cyber-attacks, databases have to be fortified against malicious threats like ransomware attacks, unauthorized access, and SQL injections. 

• Parameterizing queries and preparing statements prevent SQL injection attacks
• RBAC, or role-based access control, restricts access that is based on user privileges
• Using data encryption (AES-256, SSL/TLS) secures the sensitive information that is in transit and also at rest
• Regularly conduct vulnerability assessments to identify and patch loopholes in security
• WAFs and web application firewalls block SQL injection attempts that are automated 

Did you know? SQL injection attacks remain the topmost security concern among all cybersecurity threats, with 30% of all web app attacks targeting databases. 

Disaster and backup recovery strategies 

Data loss from hardware failure, human error, or cyberattacks can result in catastrophe for the company. A robust backup and a solid disaster recovery plan assure business continuity. 

• Automated daily backups effectively reduce data loss risk.
• Geo-redundant storage assures storage of copies of data across multiple locations.
• Point-in-time recovery, or PITR, facilitates the rollback of timestamps.
• Database replication facilitates the creation of real-time data copies for failover protection.
• Frequent disaster recovery drills will validate the backup integrity. 

The best solutions in this case are Veeam Database Recovery, Google Cloud SQL Backups, and AWS Backups. 

Web application databases – what to expect ahead 

With the continuous evolution of the database landscape and the rise of multi-cloud storages, serverless computing, and AI innovations, here is what we can expect ahead: 

Database automation powered by AI 

Artificial intelligence transforms database management by automating tasks like anomaly detection, indexing, and query tuning. This will make room for: 

• Optimization of AI-powered query for improving performance and reducing latency.
• Automation of schema evolution that adapts databases dynamically with every need of change in the application.
• Real-time anomaly detection for preventing security breaches and performance bottlenecks.
• Self-healing databases will proactively adjust configurations after predicting failures. 

Serverless databases will be on the rise 

The emergence of serverless databases will allow developers to focus solely on logic applications and scale dynamically on demand. As a result, infrastructure management will gradually decrease. 

• Auto-scaling will adjust resources in real time without the need for any manual intervention.
• The pay-per-use pricing model will optimize costs by charging for active queries only.
• Instant provisioning will make room for rapid deployment without any server configurations.
• The event-powered architecture will facilitate seamless microservice integration. 

Popular options: Azure Cosmos DB, Google Firebase Firestore, AWS Aurora Serverless 

The adoption of multi-cloud databases will continue to rise 

Businesses are increasingly reaching out to multiple cloud providers to enhance the resilience of their databases, optimize costs, and avoid vendor lock-in. Here's what we can expect to see: 

• Cross-cloud synchronization of data which assures seamless access across various platforms.
• Disaster recovery solutions are implemented across different regions of the cloud to minimize downtime.
• Deployment of hybrid cloud to balance scalability and on-premises control.
• Compliance with data sovereignty is needed to ensure optimal alignment with regional regulations. 

IDC reports that by this year, nearly 75% of enterprises will implement a multi-cloud strategy for their database deployments. 

As we can see, the future of web application databases lies in multi-cloud resilience, serverless flexibility, and AI-powered automation. Enterprises that adapt to these trends will gain a competitive edge in cost efficiency, security, and scalability. 

Proquantic Software – powering enterprise web applications with database solutions 

Proquantic's custom software development services empower enterprises to make data-powered decisions by integrating the best-suited databases in their web apps. Whether it's a scalable NoSQL solution like Dynamo DB or MongoDB for handling massive datasets or high-performing SQL databases like MySQL or PostgreSQL for seamless management of structured data, we ensure that our clients get a database infrastructure that meets their needs. 

With a focus on seamless integration, security, and scalability, our custom solutions are at par with the industry's best practices. They future-proof enterprise systems, improve app speed, and optimize data management. 

By leveraging strong data security measures, cloud-based architectures, and AI-driven automation, we assist industries in staying competitive and relevant in the dynamic digital landscape. 

Why enterprises trust us for the best web app databases 

With Proquantic, our clients get a strategic data infrastructure which brings long-term business success with enhanced security and performance. Here's what we offer: 

1. Hybrid and cloud-native solutions: Deploy databases on Google Cloud, Azure, and AWS and ensure cost-effectiveness and high availability.
2. Flexibility and scalability: Whether enterprises require ACID-compliant relational databases or a NoSQL solution, our custom architectures are ready for future growth.
3. Security-centric approach: We implement compliant-driven security protocols, robust encryption, and real-time threat monitoring to safeguard critical enterprise data.
4. Smooth integration: We seamlessly integrate databases with third-party tools, cloud environments, and enterprise systems to provide a seamless and connected experience.
5. Database focused development: Proquantic's approach promises that every application will be developed using a database structure that improves performance and scalability. 

Conclusion 

Databases make the core of web applications. They ensure seamless performance, security, and data management. As web applications become more complex, it is crucial to select the right one for unparalleled scalability and efficiency. A wide range of SQL and NoSQL databases meet the needs of different applications. 

Among them, Microsoft SQL, PostgreSQL, and MySQL remain the preferred choices in 2025 for their transactional integrity and structured data. Cassandra, Redis, and MongoDB offer high scalability and flexibility for data-intensive modern applications. 

Several factors are involved when choosing a database, like budget constraints, security needs, application size, data structure, and more. NoSQL databases are ideal for high-volume and dynamic data processing, whereas SQL databases are best for relational and structured data with high consistency requirements. 

Also, serverless databases and AI-powered automation are reforming the way web applications process data and making cloud-based solutions more relevant for enterprises that seek cost efficiency and agility. The best database, ultimately, is the one that will align with your business's unique demands, ensuring long-term sustainability, scalability, and optimal performance. 

Frequently Asked Questions (FAQs) 

Which database is best for web applications in 2025? 

Whether a database suits your needs depends entirely on the nature of the web application. PostgreSQL and MySQL widely use structured data, whereas DynamoDB, MongoDB, etc., are used for their high scalability. In general, enterprise applications depend on Oracle or Microsoft SQL Server for their high performance and robust security. 

How do I choose between SQL and NoSQL? 

You may choose a NoSQL or SQL database based on the application's needs and data structure. An SQL database is the right fit for applications that need complex queries, strong consistency, and structured data, while NoSQL databases are great for managing semi-structured or unstructured data and offer better flexibility and scalability. 

What is the fastest database for web apps? 

Redis is considered one of the speediest databases, thanks to its in-memory data processing. MySQL and PostgreSQL also deliver high-speed performance with query optimization and proper indexing, making them the right databases for speed-sensitive apps. 

Are cloud databases better than traditional ones? 

On-premises databases provide robust security and great control and are preferred in enterprises with strict compliance needs. Cloud-based databases, on the other hand, have less infrastructure costs, automatic updates, and scalability, which makes them ideal for modern applications. What you choose depends entirely on your organizational scalability and priority goals.