About Database

About Database

Database Defined 

A database is an organized collection of structured information, or data, typically stored electronically in a computer system. A database is usually controlled by a database management system (DBMS). The data and the DBMS, along with the associated applications, are referred to as a database system, often shortened to just the database.  Data within the most common types of databases in operation today is typically modeled in rows and columns in a series of tables to make processing and data querying efficient. The data can then be easily accessed, managed, modified, updated, controlled, and organized. Most databases use structured query language (SQL) for writing and querying data.


Types of Database

There are many types of databases.

1. Relational Databases (RDBMS)

  • Structure: Tables with rows and columns.  
  • Uses: Structured data, relationships between entities.  
Examples:  
  • MySQL  
  • PostgreSQL, 
  • Oracle Database  
  • Microsoft SQL Server  

2. NoSQL Databases 

  • Structure: Non-tabular (key-value, document, column-family, or graph).  
  • Uses: Unstructured or semi-structured data, big data, real-time apps.  

Types:  

  • Document: MongoDB, CouchDB 
  • Key-Value: Redis, DynamoDB  
  • Column-Family: Cassandra, HBase  
  • Graph: Neo4j, ArangoDB  

3. In-Memory Databases 

  • Structure: Data stored in RAM for fast access.  
  • Uses: Caching, real-time analytics.  

Examples: 

  • Redis, Memcached  

4. Object-Oriented Databases 

  • Structure: Stores data as objects, similar to object-oriented programming.  
  • Uses: Applications using OOP languages.  

Examples: 

  • db4o, ObjectDB  

5. Time-Series Databases 

  • Structure: Optimized for timestamped data.  
  • Uses: IoT, monitoring, and financial data.  

Examples: 

  • InfluxDB, TimescaleDB, Prometheus

6. Graph Databases

  • Structure: Notes and Edges (Relationships)
  • Uses: Social network, Recommender engines
Example:
  • Neo4j
  • JanusGraph

7. NewSQL Database

  • Structure: Similar to SQL, but with the scalability of NoSQL.
  • Uses: High-traffic applications that need consistency.

Examples: 
  • Google Spanner
  • CockroachDB
  • VoltDB

8. Cloud Database:

  • Structure: Hosted and cloud platform
  • Uses: scalable managed service

Examples:

  • Amajon RDS
  • Google Cloud Firestore

Mention the difference between the conventional file system and a database management system:

The major differences between the file management system and database management system (DBMS) are as follows −

File Management System

  • Small system
  • Relatively cheap. 
  • Few files. 
  • Need an individual application program to perform any operation on data files. Transaction management is difficult. 
  • Programming is done using COBOL, C, and PASCAL, also known as 3GL. 
  • Simple structure
  • No Security. 
  • Simple, primitive backup or recovery. 
  • Single user. 
  • Duplication of data cannot be minimized. 
  • Data Consistency is lower. 
  • It stores the unstructured data.

Database Management System

  • Many files.  
  • Relatively expensive.   
  • Learge system
  • Using a single command, any operation can be performed on data files.  
  • Transaction management is easy.  
  • Programming is done using SQL, which is a 4GL.  
  • Complex Structure.  Rigorous Security.  
  • Complex and sophisticated backup or recovery.  
  • Multiple users  Duplication of data can be minimized.  
  • Data consistency is more important because of normalization.  
  • It is used for storing structured data.

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