Entities and Attributes in Databases for LinkedIn

Entities in a LinkedIn database represent various aspects of user profiles, connections, job postings, content, and interactions, while attributes describe their characteristics. Common entities and their attributes include:

User Table

UserID (Primary Key): Unique identifier for each user.
Name, Email: User’s name and email address.
PasswordHash: Securely hashed password for user authentication.
Employment History: Details of user’s employment history, including company names, positions, and dates.
Education: User’s educational background, including degrees, institutions, and fields of study.

Connection Table

ConnectionID (Primary Key): Unique identifier for each connection.
UserID: Identifier for the user initiating the connection.
ConnectedUserID: Identifier for the user being connected with.
ConnectionType: Type of connection (e.g., colleague, friend, recruiter).

Job Posting Table

JobID (Primary Key): Unique identifier for each job posting.
EmployerID: Identifier for the company posting the job.
Title, Description: Title and description of the job opportunity.
Location: Location of the job position.
Requirements: Skills and qualifications required for the job.

Post Table

PostID (Primary Key): Unique identifier for each post.
UserID: Identifier for the user creating the post.
Content: Text content of the post (e.g., article, update).
Likes, Comments: Count of likes and comments on the post.

Message Table

MessageID (Primary Key): Unique identifier for each message.
SenderID, ReceiverID: Identifiers for the sender and receiver of the message.
Content: Text content of the message.
Timestamp: Date and time when the message was sent.

How to Design a Database For LinkedIn?

LinkedIn is a big networking site that connects millions of people for jobs and professional relationships. To make this work smoothly, LinkedIn uses a smart database system that handles user data, connections, job listings, and shared content efficiently. In this article, we’ll explore how databases are designed for professional networking services like LinkedIn.