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Unraveling the Web: Navigating Databases in Web Technology
Latest   Machine Learning

Unraveling the Web: Navigating Databases in Web Technology

Last Updated on April 25, 2024 by Editorial Team

Author(s): Bhavesh Agone

Originally published on Towards AI.

Data is the foundation of how today’s websites and apps function. Items in your shopping carts, comments on all your posts, and changing scores in a video game are examples of information stored somewhere in a database. Which begs the question what is a database? In a broad context, a database is any logically modeled collection of information but in the context of websites it is an essential component that enables websites to store, manage, and retrieve all kinds of data efficiently making the websites dynamic.

Types of Databases:

There are many different types of databases. The performance of the website is directly proportional to whether or not the developers have selected the right database to meet the needs and scales of the website operations

1. Relational databases — The name comes from the way data is stored in the form of related tables, developed by IBM in the 1970s. Since then, it has been helping businesses organize, manage and relate data. The tables store data in the form of rows and columns. These relational databases are compliant with the ACID properties and work well with structured data. To create, update, and manage a relational database, we use a relational database management system that most commonly runs on Structured Query Language (SQL). These databases offer consistency through their well-structured schemas but fail to scale very well

2. NoSQL databases — NoSQL is a vast category that includes all databases that do not use SQL as their primary data access language. Contrary to relational databases, these do not conform to a pre-defined schema, operate in distributed clusters, and store unstructured or semi-structured data thus they are also referred to as non-relational databases. These databases do not comply with ACID properties which poses a threat to the consistency of the data stored in the database. Developers use non-relational databases for applications that need to scale efficiently and quickly because of their ability to process large volumes of data with very low latency.

3. New SQL databases — NewSQL is a modern form of relational database system that sits between SQL and NoSQL. Coined in 2011, it was designed to function in distributed clusters similar to NoSQL databases, they have a relational model that complies with ACID properties and supports SQL query semantics. Therefore offering capabilities to handle large volumes of data in real time, without sacrificing consistency or reliability. NewSql is still a newer technology, so it may not have a complete arsenal of tools and functionalities provided by preexisting systems.

Factors To Consider When Selecting Database (Relational vs NoSQL) For Web Applications:

1. Data Model And Schema Flexibility

Relational Databases: These are the best for structured data, with predefined schemas and complicated relationships between entities.

NoSQL Databases: Designed for semi-structured or unstructured data that have flexible schemas, enabling quick development and schema evolution.

2. Scalability Requirements

Relational Databases: Hardware resources typically limit vertical scalability while horizontal scalability might require complex sharding or replication setups.

NoSQL Databases: Have been designed to be horizontally scalable so as to allow you distribute your data across multiple nodes effortlessly.

3. Performance Considerations

Relational Databases: Optimized for transactional workloads that need ACID compliance; suitable for applications requiring complex queries and joins.

NoSQL Databases: Targeted towards high throughput and low latency during read/write operations, which makes them perfect for real-time analytics, caching, high volume transactional workloads etc.

4. Consistency And Availability

Relational Databases: Emphasize strong consistency and ACID transactions at the cost of possible performance and availability trade-offs to ensure data integrity.

NoSQL Databases: They prioritize availability as well as partition tolerance over strong consistency in order to provide eventual consistency model for distributed systems.

5. Development and Maintenance Complexity

Relational Databases: They require strict adherence to defined schemas, complex normalization, and querying using SQL. For applications with well-defined data structures and multi-faceted relationships.

NoSQL Databases: That is why they tend to have more flexible schemas as well as simpler query languages for reducing development overheads, enabling agile iterations.

6. Use Case and Workload Patterns

Relational Databases: However, they work best for architectures with transactional requirements, complex data relationships, and strong consistency such as these found in e-commerce platforms, financial systems or ERP applications.

NoSQL Databases: Furthermore NoSQL databases are ideally suited for use cases that involve rapid prototyping where there is an urgent need for scalability at a given point in time or real-time analytics or unstructured/semi-structured data like social networks, IoT platforms or content management systems.

Some of the databases in Web Technology:

A database is necessary for every organization in order to organize and keep its core information. A database management system software comes to the rescue to offer such a service. The rise of microservices, cloud distributed apps, semi-structured data, big data, low latency data, and so forth has led to the addition of various NoSQL, NewSQL, and cloud databases to the traditional SQL list of the most popular databases.

Some of the databases for use with web applications are listed here:

1. MySQL: MySQL is a dependable database that has gained popularity as a result of web developers’ relentless pursuit of stability and rapid development.
The most recent version of MySQL, version 8.0, cannot be covered by the free SQL database and is written in C and C++.
Because of its functional characteristics, flexible GPL license, and updated versions, MySQL became widely used very quickly.

2. MariaDB: An RDMS that complies with the MySQL standard is MariaDB. You can switch your MySQL server with it rather often without having to change the code.
Compared to MySQL, it is more concentrated on the local area network.
It is a structure that makes working with large datasets faster and easier by providing columnar capacity with widely distributed parallel data.

3. Oracle: Oracle is a well-liked database for web applications because of its remarkable performance, scalability, and flexibility. It comes with a popular RDBMS and built-in low-level programming languages including Java, C, and C++.It processes data faster and requires less space than conventional databases.

4. PostgreSQL: Formerly known as Postgres, PostgreSQL offers a wide range of sophisticated requirements in a unified package with an easy-to-understand curve that can be adjusted and maintained beyond typical capabilities.
PostgreSQL is a C-developed database used for handling large amounts of data related to database automation tools, gaming applications, and domain registrations.

5. MongoDB: Released in 2009, MongoDB is considered the solution to the problems caused by object-oriented languages like RDBMS since it uses a different method of storing data and necessitates further application-level planning.
Therefore, MongoDB was developed to handle document data without the requirement for extra programs in order to solve this issue.

6. IBM DB2: IBM’s state-of-the-art platform is AI-driven and intended to deliver data wherever it is required.
Its tested task-ready features let you save costs and obtain a thorough picture at the same time, thanks to its multimodal capabilities that do away with the need for duplicates or moves.

7. Cassandra: Cassandra’s open technology and rich column store features enable it to easily handle massive volumes of data.
Its resilience to failures has made it a popular option for businesses in a variety of industries, making it appropriate in the event of faults or even a spike in traffic to your website.

8. Redis: Redis serves as both a caching system and a database.
It’s an in-memory, open-source store that offers a variety of structures, including streams, range searches, bitmaps, geographic indexes, hashes, lists, and sets.

9. Elasticsearch: With its automatic sharing and API features, Elasticsearch is an open-source, full-text search engine built on Lucene that can handle horizontal scalability with ease.
Whether logging or checking figures, it has the energy and aptitude to store and handle a wide range of data.

Integrating Web Technologies with Databases:

In most cases in the web development, to get access to and alter the database they have to go through a backend server that employs programming languages such as Python, JavaScript and PHP. Django, Flask, Express.js and Laravel are frameworks which make it easier for people to interact properly with databases.

-Object-Relational Mapping (ORM):

Bridging the gap between object-oriented programming paradigm and relational databases are ORM libraries like SQLAlchemy (for Python) and Sequelize (for Node.js). Developers can use these libraries to interact with database entities as native language objects thereby hiding the SQL intricacies and database interaction.


Web applications’ RESTful APIs are the intermediaries between frontend and backend which facilitate smooth coordination and flow of data from one part of a system to another. In accordance with REST, clients can perform Create, Read, Update, and Delete (CRUD) operations on the underlying database using HTTP requests.

Best Practices in Database Management for Web Technologies:

1. Normalize Data: This will help to remove redundancy and also maintain the integrity of the information.

2. Indexing: To enhance query performance, index should be used particularly for frequently accessed fields.

3. Backup and Recovery: Regular backup and recovery procedures will ensure that data is safe.

4. Security Measures: Implement security mechanisms which include authentication, authorization and encryption to protect sensitive data.

5. Scalability: The database shall be designed in such a way that it can be scaled horizontally or vertically when there is more data and many users.


In conclusion, the choice of database to use in a web application is an important one as it has a great impact on its performance, scalability and complexity of development. However, careful examination of issues like scalability requirements, data model, performance considerations, complexity trade-offs between consistency and availability, development complexity alongside operational complexity as well as cost consideration can enable you to make an informed decision that suits your project’s goals and requirements.

Ultimately, however, the objective is to pick out a database system that caters to immediate necessities and growing needs over time. Through the application of a consistent approach to database selection, which looks at technical aspects as well as commercial aspects, it is possible to develop a strong grounding for scalable, resilient, and economical web applications that provide value-addition to your users or stakeholders.

Please feel free to share your thoughts in the comment section. Your suggestions are always welcome.

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Published via Towards AI

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