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Binoy Vijayan
Binoy Vijayan

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Introduction to Database Awareness

A database is a structured collection of data organised in a way that allows efficient retrieval, storage, and management of information. Databases are a fundamental component of many software applications, providing a systematic and organised approach to storing and retrieving data.

Databases can be categorised based on various criteria, including their data model, architecture, and use cases.

Here's a list of some common categories of databases:

1. Relational Databases (RDBMS):

Organises data into tables with rows and columns, enforces relationships between tables, and uses SQL for querying and managing data.

Examples: MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server.

More details about RDBMS

2. NoSQL Databases:

a. Document-Oriented Databases:

Stores data in flexible, JSON-like documents.

Examples: MongoDB, CouchDB.

b. Key-Value Stores:

Stores data as key-value pairs.

Examples: Redis, Amazon DynamoDB.

c. Wide-Column Stores:

Organises data in columns and is used in distributed and scalable environments.

Examples: Apache Cassandra, HBase.

d. Graph Databases

Stores and queries data with complex relationships using graph structures.

Examples: Neo4j, Amazon Neptune.

3. In-Memory Databases:

Stores data primarily in RAM for fast data access.

Examples: Redis, VoltDB.

4. NewSQL Databases:

Aims to combine the scalability of NoSQL databases with ACID compliance for distributed transactions.

Examples: Google Spanner, CockroachDB.

5. Columnar Databases:

Stores data in columns, optimised for analytical queries and data warehousing.

Examples: Amazon Redshift, Google Bigtable.

6. Time-Series Databases:

Designed to efficiently handle and query data with timestamp information, commonly used in monitoring and IoT applications.

Examples: InfluxDB, Prometheus.

7. Spatial Databases:

Manages and queries spatial or geographic data, supporting features like points, lines, and polygons.

Examples: PostGIS (extension for PostgreSQL), Oracle Spatial.

8. Object-Oriented Databases:

Stores data in the form of objects, allowing for a more natural representation of complex data structures and relationships.

Examples: db4o, ObjectDB.

9. Multimodel Databases:

Supports multiple data models (e.g., document, graph, key-value) within a single database engine.

Examples: ArangoDB, OrientDB.

10. Blockchain Databases:

Stores data in a decentralised and tamper-resistant manner using blockchain technology.

Examples: Hyperledger Fabric, Ethereum.

11. Embedded Databases:

Lightweight databases integrated directly into an application.

Examples: SQLite, H2 Database.

12. Cloud-Based Databases:

Hosted and managed in the cloud, providing scalability, automated backups, and easy integration with other cloud services.

Examples: Amazon RDS, Azure SQL Database, Google Cloud Firestore.

This list provides an overview of different database categories, and each category serves specific use cases and requirements. The choice of a database type depends on factors such as data model, scalability, performance, and the nature of the application being developed.

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