What is Database?

A database is a structured collection of data organized for efficient retrieval, storage, and management. It’s essentially an organized system where data can be easily accessed, managed, and updated. Databases are fundamental components of information systems and are used in various applications across industries such as banking, healthcare, e-commerce, education, and more.

Types of Database

There are several types of databases but we currently focuses on two types:

1. Relational database
2. Non-Relational database

A Relational Database Management System (RDBMS)

Relational databases typically consist of tables, each containing rows and columns. Each row represents a record, and each column represents a specific attribute or field within that record. By organizing data into tables, databases provide a structured way to store and retrieve information.

Relational databases, such as MySQL, PostgreSQL, and Oracle, are the most common type and use structured query language (SQL) for querying and managing data.

RDBMS Terminology

1. Database: A database is a collection of tables, with related data.
2. Table: A table is a matrix with data. A table in a database looks like a simple spreadsheet.
3. Column: One column (data element) contains data of one and the same kind, for example the column postcode.
4. Row: A row (= tuple, entry or record) is a group of related data, for example the data of one subscription.
5. Redundancy: Storing data twice, redundantly to make the system faster.
6. Primary Key: A primary key is unique. A key value can not occur twice in one table. With a key, you can find at most one row.
7. Foreign Key: A foreign key is the linking pin between two tables.
8. Compound Key: A compound key (composite key) is a key that consists of multiple columns, because one column is not sufficiently unique.
9. Index: An index in a database resembles an index at the back of a book.
10. Referential Integrity: Referential Integrity makes sure that a foreign key value always points to an existing row.

Non-Relational Database (No-SQL)

NoSQL databases, on the other hand, offer more flexibility and scalability and are often used for handling large volumes of unstructured or semi-structured data.

Non-Relational databases (No-SQL) such as MongoDB is the most common type and use No-SQL for querying and managing data.

1. Flexible Data Models: NoSQL databases accommodate various types of data structures, including key-value pairs, documents, wide-column stores, and graphs. This flexibility allows developers to choose the most suitable data model for their application’s needs. For example, a document-oriented NoSQL database like MongoDB stores data in JSON-like documents, making it easy to work with data in a hierarchical structure.
2. Scalability: NoSQL databases are designed to scale horizontally, meaning they can distribute data across multiple servers or clusters to handle increasing loads. This horizontal scalability makes NoSQL databases well-suited for web applications, big data analytics, and other scenarios with rapidly growing datasets and user bases.
3. High Performance: NoSQL databases often prioritize performance and low latency by using techniques like in-memory caching, sharding, and eventual consistency. By relaxing ACID (Atomicity, Consistency, Isolation, Durability) transaction guarantees, NoSQL databases can achieve higher throughput and lower response times for read and write operations.
4. Polyglot Persistence: NoSQL databases embrace the concept of polyglot persistence, which means using multiple database technologies within a single application based on specific data requirements. This approach allows developers to leverage the strengths of different database types to efficiently store and process diverse types of data.
5. Use Cases: NoSQL databases are commonly used in scenarios such as real-time analytics, content management systems, e-commerce platforms, mobile apps, gaming, IoT (Internet of Things), and social networks. They excel in handling unstructured or semi-structured data, such as user-generated content, sensor data, log files, and multimedia files.
6. Types of NoSQL Databases: NoSQL databases are classified into several types based on their data models, including:
   • Document-oriented databases (e.g., MongoDB, Couchbase)
   • Key-value stores (e.g., Redis, Amazon DynamoDB)
   • Column-family stores (e.g., Apache Cassandra, HBase)
   • Graph databases (e.g., Neo4j, Amazon Neptune)
7. Challenges: While NoSQL databases offer advantages in scalability and flexibility, they also come with challenges such as eventual consistency, lack of standardized querying (compared to SQL), and the need for careful consideration of data modeling and indexing strategies.

Overall, databases play a crucial role in modern information systems by providing a reliable and efficient way to store, retrieve, and manage data, thereby enabling organizations to make informed decisions and perform various operations effectively.