Skip to main content

Schema and Instance in DBMS

Schema and Instance in DBMS

1. Instances :
Instances are the collection of information stored at a particular moment. The instances can be changed by certain operations as like addition, deletion of data. It may be noted that any search query will not make any kind of changes in the instances.

Example –
Let’s say a table teacher in our database whose name is School, suppose the table has 50 records so the instance of the database has 50 records for now and tomorrow we are going to add another fifty records so tomorrow the instance have total 100 records. This is called an instance.

2. Schema :
Schema is the overall description of the database. The basic structure of how the data will be stored in the database is called schema.

Schema and Instance in DBMS


Schema is of three types: Logical Schema, Physical Schema and view Schema.
  1. Logical Schema – It describes the database designed at logical level.
  2. Physical Schema – It describes the database designed at physical level.
  3. View Schema – It defines the design of the database at the view level.

Example –
Let’s say a table teacher in our database name school, the teacher table require the name, dob, doj in their table so we design a structure as :

Teacher table
name: String
doj: date
dob: date 

Above given is the schema of the table teacher.


Difference between Schema and Instance :


Schema
  • It is the overall description of the database.
  • Schema is same for whole database.
  • Does not change Frequently.
  • Defines the basic structure of the database i.e how the data will be stored in the database.

Instance
  • It is the collection of information stored in a database at a particular moment.
  • Data in instances can be changed using addition, deletion, updation.
  • Changes Frequently.
  • It is the set of Information stored at a particular time.

Comments

Popular posts from this blog

All About Microservices Architecture

All About Microservices Architecture **Microservices Architecture** is an approach to software development where a large application is broken down into smaller, independent services that can operate and be deployed independently. Instead of building a monolithic application, which is a single, tightly-integrated unit, microservices architecture divides the functionality into separate services that communicate with each other through well-defined APIs (Application Programming Interfaces). Key characteristics of microservices architecture include: 1. **Modularity:** Each microservice represents a specific business capability and can be developed, deployed, and scaled independently. 2. **Independence:** Microservices are autonomous, meaning they can be developed, deployed, and updated without affecting the entire system. This independence allows for faster development cycles. 3. **Scalability:** Since each service is independent, you can scale only the specific microservices that require...

Relational Calculus

Relational Calculus There is an alternate way of formulating queries known as Relational Calculus. Relational calculus is a non-procedural query language. In the non-procedural query language, the user is concerned with the details of how to obtain the end results. The relational calculus tells what to do but never explains how to do. Most commercial relational languages are based on aspects of relational calculus including SQL-QBE and QUEL. Why it is called Relational Calculus? It is based on Predicate calculus, a name derived from branch of symbolic language. A predicate is a truth-valued function with arguments. On substituting values for the arguments, the function result in an expression called a proposition. It can be either true or false. It is a tailored version of a subset of the Predicate Calculus to communicate with the relational database. Many of the calculus expressions involves the use of Quantifiers. There are two types of quantifiers: Universal Quantifiers: The univer...

Natural Language Processing (NLP)

What is Natural Language Processing (NLP) ? Natural Language Processing (NLP)* is a field of artificial intelligence (AI) that focuses on the interaction between computers and humans using natural language. It involves the development of algorithms and models that enable computers to understand, interpret, and generate human language. Here are key aspects of NLP: 1. *Text Understanding:* NLP systems aim to comprehend the meaning of written or spoken language. This involves tasks such as text classification, sentiment analysis, and named entity recognition. 2. *Speech Recognition:* NLP extends to processing spoken language, converting audio signals into text. This technology is used in voice assistants, transcription services, and more. 3. *Language Generation:* NLP systems can generate human-like text. This is employed in chatbots, language translation services, and content generation. 4. *Machine Translation:* NLP is fundamental to machine translation systems that enable the automatic...