Social networks have fundamentally changed how billions of people connect, share, and interact online. Building a scalable social platform requires careful consideration of complex technical challenges like handling massive user data, enabling real-time interactions, managing content delivery, and ensuring high availability across global regions.
This article will look at the key architectural components and design decisions needed to build a social network that can support millions of users. We’ll examine core features like news feeds, friend relationships, content storage, and notification systems, along with scalability, performance, and reliability considerations that shape modern social platforms.
The Core Components
A typical social network architecture can be broken down into many key components:
1. Frontend:
User Interface (UI): Web and mobile applications that allow users to interact with the platform.
Web App: Developed using modern web frameworks like React, Angular, or Vue.
Mobile App: Native (iOS and Android) or cross-platform (e.g., Flutter, React Native).
API Calls: Communicate with the backend via RESTful or GraphQL APIs.
2. Backend:
Web Servers (Application Layer):
Microservices Architecture: Split functionalities into multiple services to allow for scalability and fault tolerance.
Languages & Frameworks: Node.js, Java, Python, Ruby on Rails, etc.
API Gateway: For routing, load balancing, and API management (e.g., Kong, NGINX, AWS API Gateway).
Core Services:
User Service: Manages user profiles, authentication, and authorization.
Feed Service: Generates and serves posts on the user’s feed.
Friendship Service: Manages friend requests, relationships, and social graph.
Post/Content Service: Manages the creation, editing, deletion, and retrieval of posts.
Messaging Service: Handles private messages between users, including real-time communication (using WebSockets, for instance).
Notification Service: Sends notifications about new posts, messages, friend requests, etc.
Search Service: Provides search capabilities to find users, posts, groups, etc. (Could use Elasticsearch or similar tools).
Media Service: Handles media uploads and serves images, videos, etc. (e.g., using a CDN for media delivery).
Database Layer:
Relational Databases (SQL): For user profiles, relationships, posts (e.g., MySQL, PostgreSQL).
NoSQL Databases: For feeds and messages, where quick read/write performance is required (e.g., MongoDB, Cassandra).
Search Database: For full-text search (e.g., Elasticsearch).
Cache Layer: Use Redis or Memcached for caching frequently accessed data (e.g., user feeds, notifications).
Data Warehouse: Store logs, analytics data, and large-scale user activity data (e.g., BigQuery, Snowflake).
Message Queues:
RabbitMQ, Kafka, or SQS to manage asynchronous processing (e.g., processing posts, notifications, and messaging queues).
3. Infrastructure:
Load Balancers: Distribute incoming traffic across multiple servers to balance load (e.g., HAProxy, AWS ELB).
Kubernetes: Container orchestration for managing microservices and ensuring scalability and fault tolerance.
Docker: Containerization of microservices for easier deployment and scaling.
4. Third-party Integrations:
Authentication Services: Use OAuth or SSO for third-party logins (Google, Facebook, etc.).
Payment Gateways: If there’s a monetization model (e.g., Stripe, PayPal).
Analytics: Tools like Google Analytics or custom analytics service to track user behavior and engagement.
5. Security:
Authentication & Authorization:
OAuth2 for third-party login (Google, Facebook).
JWT (JSON Web Tokens) for session management.
Multi-factor Authentication (MFA) for additional security.
Data Encryption: Encrypt sensitive data at rest and in transit using TLS/SSL.
Access Control: Role-based access control (RBAC) for restricting access to certain features (admin, regular user, etc.).
Architectural Diagram
This diagram provides an overview of the major components and their interactions in a social network system architecture.
graph LR
subgraph Frontend
A["User Interface (Web & Mobile App)"]
end
subgraph API_Gateway
B[API Gateway]
end
subgraph Backend
C[User Service]
D[Feed Service]
E[Post Service]
F[Friendship Service]
G[Messaging Service]
H[Notification Service]
I[Search Service]
J[Media Service]
end
subgraph Infrastructure
Q[Load Balancer]
R[Kubernetes]
S[Docker]
end
subgraph Databases
K["Relational DB (SQL)"]
L["NoSQL DB (MongoDB)"]
M["Search DB (Elasticsearch)"]
N["Cache (Redis)"]
O["Data Warehouse (BigQuery)"]
P["Media Storage (CDN/S3)"]
end
subgraph Third_Party_Integrations
T["OAuth (Google/Facebook)"]
U["Payment Gateway (Stripe)"]
V["Analytics (Google Analytics)"]
end
A --> B
B --> C
B --> D
B --> E
B --> F
B --> G
B --> H
B --> I
B --> J
C --> K
D --> L
E --> L
F --> L
G --> L
H --> K
I --> M
J --> P
J --> N
P --> Q
Q --> R
R --> S
C --> T
E --> U
H --> V
D --> N
F --> K
G --> O
A -.-> Q
C -.-> Q
D -.-> Q
E -.-> Q
F -.-> Q
G -.-> Q
H -.-> Q
I -.-> Q
J -.-> Q
Frontend: The user interacts with the Web & Mobile apps, which communicate through the API Gateway to the backend services.
Backend: Core services handle various responsibilities such as user profiles, feeds, posts, messaging, notifications, and search.
Databases: Different types of databases store various kinds of data—relational for user info, NoSQL for high performance reads/writes, search for full-text search, and cache for frequently accessed data.
Infrastructure: Load balancing, container orchestration (Kubernetes), and Docker are used for scalability, deployment, and fault tolerance.
Third-party Integrations: Authentication, payment gateways, and analytics for extending the platform’s functionality.
Media Upload and Storage: Media Service is responsible for handling media uploads. Uploaded media (e.g., images, videos) is stored in Media Storage (CDN/S3). Redis (Cache) is used to cache frequently accessed media.
Data Flow
The data flow architectures shows information moves between different system components. This section examines the critical paths data takes from user interactions to storage, processing, and delivery - including post creation, content distribution, and real-time updates. Understanding these flows is essential for building a responsive and reliable social platform that can handle millions of concurrent users while maintaining data consistency and low latency.
1. User Signup/Authentication
The user registers via the frontend (mobile/web), which makes an API call to the user service to store user details. The user’s session is created using JWT.
sequenceDiagram
participant User as User (Frontend)
participant UI as User Interface
participant API as API Gateway
participant Auth as Authentication Service
participant DB as User Database
User->>UI: Fills Signup/Login Form
UI->>API: Sends Form Data (Username, Password, etc.)
API->>Auth: Forward Form Data for Authentication
Auth->>DB: Check/Store User Credentials
DB-->>Auth: Returns User Exists/Success or Create New User
Auth-->>API: Returns Success/Failure with Token (JWT)
API-->>UI: Send Authentication Token
UI-->>User: Display Success or Error Message
User->>UI: Uses Token for Subsequent Requests
UI->>API: Send Token with API Requests
API->>Auth: Validates Token for Authentication
Auth-->>API: Returns Valid/Invalid
API-->>UI: Grants Access if Valid
User fills the signup or login form on the frontend (web or mobile app).
The form data is sent to the API Gateway, which routes the request to the Authentication Service.
Authentication Service checks or stores the credentials in the user database, verifying if the user exists or creating a new one if signing up.
The Authentication Service responds with a success or failure message and issues a JWT (JSON Web Token) if successful.
The token is sent back to the frontend, and subsequent requests use this token for authorization.
The token is validated by the authentication service on every request to verify the user’s identity before granting access to protected resources.
2. Posting Content
The user uploads a post with text or media. The frontend sends the request to the post service, which stores the post in the database. The feed service updates the user’s feed and relevant friends’ feeds.
The below diagram captures the complete flow of data and services involved when a user posts content, including media uploads and feed updates.
sequenceDiagram
participant User as User (Frontend)
participant UI as User Interface
participant API as API Gateway
participant PostService as Post Service
participant MediaService as Media Service
participant FeedService as Feed Service
participant PostDB as Post Database
participant MediaCDN as Media Storage (CDN)
participant FeedDB as Feed Database
User->>UI: Create Post with Text/Media
UI->>API: Send Post Request (Text/Media)
API->>PostService: Forward Post Data
PostService->>PostDB: Store Post Metadata (Text, Timestamp)
PostService->>MediaService: Send Media Data for Upload
MediaService->>MediaCDN: Upload Media to CDN
MediaCDN-->>MediaService: Return Media URL
MediaService-->>PostService: Return Media URL
PostService-->>API: Post Created (Post ID, Media URL)
API-->>UI: Return Success (Post ID, Media URL)
PostService->>FeedService: Notify Feed Service (New Post)
FeedService->>FeedDB: Update User's Feed
FeedService->>FeedDB: Update Friends' Feeds
FeedDB-->>FeedService: Feeds Updated
FeedService-->>UI: Feed Updated for User and Friends
User creates a post with text and/or media on the frontend (Web/Mobile App).
The frontend sends the post data to the API Gateway, which routes it to the Post Service.
Post Service stores the post metadata (text, timestamps, and post details) in the Post Database.
If the post includes media, the Post Service sends the media to the Media Service, which uploads the media to a CDN (Content Delivery Network) and returns the media URL.
The Post Service responds back to the frontend with a success message and the Post ID and Media URL.
The Post Service notifies the Feed Service about the new post.
The Feed Service updates the feeds of the user and their friends by interacting with the Feed Database.
The updated feeds are sent back to the user, showing the post in the feed and ensuring friends’ feeds are updated as well.
3. Real-time Messaging
The user sends a message via WebSocket, which the messaging service handles in real time.
The below sequence demonstrates how real-time messaging works, leveraging WebSocket connections for instant, two-way communication between users. The message queue is optional and can be used to handle high traffic and ensure reliable delivery.
sequenceDiagram
participant User as User (Frontend)
participant WebSocket as WebSocket Connection
participant MessagingService as Messaging Service
participant MessageQueue as Message Queue (Optional)
participant Receiver as Receiver (Frontend)
participant DB as Message Database
User->>WebSocket: Send Message (Text/Media)
WebSocket->>MessagingService: Forward Message via WebSocket
MessagingService->>DB: Store Message in Database
alt With Message Queue
MessagingService->>MessageQueue: Add Message to Queue
MessageQueue->>Receiver: Deliver Message via WebSocket
else Without Message Queue
MessagingService->>Receiver: Deliver Message via WebSocket
end
DB-->>MessagingService: Acknowledge Message Stored
MessagingService-->>User: Acknowledge Message Sent
Receiver-->>User: Message Delivered Notification
User sends a message (text or media) via the frontend app (Web or Mobile). This communication happens through a WebSocket connection.
The WebSocket connection forwards the message to the Messaging Service in real time. WebSockets provide a persistent connection, allowing messages to be sent instantly.
The Messaging Service stores the message in the Message Database. This ensures the message is persisted for history or future retrieval.
Depending on the architecture:
With Message Queue: The message is added to a message queue (e.g., RabbitMQ, Kafka) to ensure reliable delivery and asynchronous processing. The message is then delivered to the intended recipient via their WebSocket connection.
Without Message Queue: The Messaging Service directly delivers the message to the recipient through their active WebSocket connection.
The Message Database acknowledges that the message has been successfully stored.
The Messaging Service sends an acknowledgment back to the user (sender), indicating the message was successfully sent.
The recipient receives the message via their WebSocket connection and gets a notification or the message directly in their chat interface in real time.
The recipient’s frontend sends a delivery notification back to the sender, confirming that the message was delivered successfully.
Notification
When a user receives a message or interaction on their post, the notification service pushes a notification to the frontend.
The below sequence demonstrates how notifications work in real time for interactions on posts or messages. The notification service is responsible for handling all interactions and delivering notifications to users efficiently.
sequenceDiagram
participant UserA as User A (Sender)
participant UI as User A's Frontend (Web/Mobile)
participant PostService as Post/Message Service
participant NotificationService as Notification Service
participant DB as Notification Database
participant UserB as User B (Receiver)
participant ReceiverUI as User B's Frontend (Web/Mobile)
UserA->>UI: Send Message / Interact with Post
UI->>PostService: Send Interaction (Message/Post Comment/Like)
PostService->>NotificationService: Notify about Interaction
NotificationService->>DB: Store Notification in Notification DB
NotificationService-->>PostService: Notification Stored
NotificationService->>ReceiverUI: Push Notification to User B
ReceiverUI-->>UserB: Display Notification in Real Time
User A initiates an interaction: User A sends a message, likes a post, or comments on a post through the frontend (Web/Mobile app).
The frontend sends the interaction data to the corresponding service (Post Service for post interactions, Message Service for direct messages).
The Post/Message Service triggers the Notification Service, informing it about the interaction that occurred (e.g., a comment on a post, a like, or a message sent).
The Notification Service stores the notification in the Notification Database for tracking purposes, so the notification can be retrieved or displayed later if necessary.
The Notification Service confirms the storage of the notification with the Post/Message Service to complete the interaction flow.
The Notification Service pushes the notification to the recipient (User B) through the frontend (WebSocket or Push Notifications).
User B’s frontend displays the notification in real time, alerting them about the interaction (message, post like, comment, etc.). l ## More Data Flows
Here are additional key data flows within the system:
1. User Profile Management
sequenceDiagram
participant User as User (Frontend)
participant APIGateway as API Gateway
participant UserService as User Service
participant SQLDB as SQL Database (Profile Info)
participant CDN as CDN (Media Storage)
participant FeedService as Feed Service
participant FriendProfile as Friend's Profile
User->>User: Submit Profile Changes (e.g., Name, Picture)
User->>APIGateway: Send Profile Change Request
APIGateway->>UserService: Forward Request to User Service
UserService->>SQLDB: Update Profile Info in SQL DB
alt Media Upload (Profile Picture)
UserService->>CDN: Upload New Profile Picture to CDN
end
SQLDB-->>UserService: Confirm Profile Info Updated
UserService-->>APIGateway: Respond with Success
APIGateway-->>User: Confirm Profile Update Success
par Feed Update
UserService->>FeedService: Notify Feed Service of Profile Update
and Friend Profile Update
UserService->>FriendProfile: Notify Friends of Updated Profile Info
end
Flow: User updates their profile (e.g., username, bio, profile picture).
Data Flow:
User submits profile changes via frontend.
Frontend sends data to the API Gateway.
API Gateway forwards the data to the User Service.
User Service updates the User Database.
Updated data is stored (e.g., profile info in SQL DB, media in CDN).
User Service responds to the frontend, confirming the changes.
Feeds and friend profiles may be updated to reflect the new info (e.g., updated profile picture).
2. Content Moderation
sequenceDiagram
participant User as User (Frontend)
participant APIGateway as API Gateway
participant ModService as Moderation Service
participant DB as Moderation Database
participant Content as Content Database (Posts/Comments)
participant PostUser as Post Owner (User Who Posted Content)
participant Reporter as Reporting User (User Who Flagged)
User->>User: Flag Post or Comment
User->>APIGateway: Send Flag Request
APIGateway->>ModService: Forward Request to Moderation Service
ModService->>Content: Fetch Flagged Post/Comment for Review
ModService->>ModService: Evaluate Content (AI or Manual Review)
alt Content Flagged as Inappropriate
ModService->>DB: Flag Content in Moderation Database
ModService->>Content: Hide or Remove Flagged Content
ModService->>PostUser: Send Notification to Content Owner
ModService->>Reporter: Send Notification to Reporting User
else Content is Safe
ModService->>Reporter: Send Notification to Reporting User (No Violation)
end
Flow: A post or comment is flagged for inappropriate content and reviewed by the moderation service.
Data Flow:
User flags a post via the frontend.
Frontend sends a flag request to the API Gateway.
API Gateway forwards the request to the Moderation Service.
Moderation Service evaluates the content (can use AI or manual review).
Moderation Service may flag the content in the database.
If flagged, content is hidden from users or removed.
Notification sent to the user who posted the content and the reporting user about the moderation result.
3. Search and Discovery
sequenceDiagram
participant User as User (Frontend)
participant APIGateway as API Gateway
participant SearchService as Search Service
participant SearchDB as Search Database (e.g., Elasticsearch)
participant ContentDB as Content Database (Posts/Users/Groups)
User->>User: Enter Search Query (Content, Friends, Groups)
User->>APIGateway: Send Search Request
APIGateway->>SearchService: Forward Search Request to Search Service
SearchService->>SearchDB: Query Search Database (Full-Text Search)
SearchDB-->>SearchService: Return Search Results (Posts/Users/Groups)
SearchService-->>APIGateway: Send Search Results to API Gateway
APIGateway-->>User: Return Search Results to Frontend
User->>User: Display Search Results (Content, Friends, Groups)
Flow: Users search for content, friends, or groups.
Data Flow:
User enters search query on the frontend.
Frontend sends the search request to the API Gateway.
API Gateway routes the request to the Search Service.
Search Service queries the Search Database (e.g., Elasticsearch, full-text search).
Search results are retrieved (posts, users, groups, etc.) from the database.
Search results are sent back to the frontend and displayed to the user.
4. Friendship Management
Flow: Users send friend requests, accept/decline requests, or unfriend each other.
Data Flow:
User sends a friend request via the frontend.
Friendship request data is sent to the API Gateway.
API Gateway forwards the request to the Friendship Service.
Friendship Service updates the Friendship Database (pending requests, acceptances, and rejections).
If accepted, feeds are updated (new posts from the friend are added to each other’s feed).
Notifications are pushed to both users (for request sent and accepted).
Frontend updates user’s friend list and displays the friend’s posts in their feed.
5. Likes, Comments, and Reactions
Flow: Users interact with posts by liking, commenting, or reacting.
Data Flow:
User interacts with a post (likes, comments, reacts).
Interaction data is sent to the API Gateway.
Post Service receives the interaction.
Interaction is stored in the Post Database (like count, comment text, etc.).
Post Service updates the Feed Service, notifying the original poster or friends.
Notification Service pushes notifications to the user who posted the content, informing them about the interaction.
Frontend updates the UI to reflect the new like, comment, or reaction.
6. Media Upload and Streaming
sequenceDiagram
participant U as User
participant F as Frontend
participant AG as API Gateway
participant MS as Media Service
participant CDN
participant DB as Post Database
%% Upload Flow
U->>F: Upload media (photo/video)
F->>AG: Send media data
AG->>MS: Forward media data
MS->>CDN: Upload media
CDN-->>MS: Return CDN URL
MS->>DB: Store media metadata
DB-->>MS: Confirm storage
MS-->>AG: Return success
AG-->>F: Return success
F-->>U: Show upload confirmation
%% Playback Flow
U->>F: Request media playback
F->>AG: Get media URL
AG->>MS: Fetch media metadata
MS->>DB: Query media data
DB-->>MS: Return metadata
MS-->>AG: Return CDN URL
AG-->>F: Return media URL
F->>CDN: Stream media
CDN-->>U: Direct media stream
Flow: Users upload media (photos, videos) or view media (playback).
Data Flow:
User uploads media (e.g., photo or video).
Frontend sends media data to the API Gateway.
API Gateway forwards the data to the Media Service.
Media Service uploads the media to the CDN (Content Delivery Network) for efficient storage and retrieval.
Media metadata (e.g., URL, file type, size) is stored in the Post Database.
Frontend retrieves the media URL for display in posts or feeds.
If media is requested for playback (e.g., videos), it is streamed directly from the CDN to the user via the frontend.
7. Analytics and Logging
Flow: System logs user interactions for analytics (e.g., number of views, engagement metrics).
Data Flow:
User interacts with the platform (views posts, clicks links, etc.).
Frontend logs interaction events and sends them to the API Gateway.
API Gateway forwards the data to the Analytics Service.
Analytics Service stores data in the Analytics Database.
Administrators or analytics dashboards retrieve data for reporting and insights.
8. User Privacy and Security
Flow: User updates privacy settings (e.g., who can see their posts).
Data Flow:
User updates privacy settings via the frontend.
Privacy settings data is sent to the API Gateway.
API Gateway forwards the settings to the User Service.
User Service updates the User Database with the new privacy settings.
Post Service and Feed Service check these settings before displaying posts or feeds to other users (e.g., restrict posts to friends-only).
Notification Service ensures notifications respect privacy settings (e.g., notifications are sent only to allowed users).
9. Group or Event Management
Flow: Users create or manage groups/events (join, invite, leave).
Data Flow:
User creates or joins a group/event via the frontend.
Frontend sends group/event request to the API Gateway.
Group/Event Service handles the request and updates the database.
Group members or event attendees are notified through the Notification Service.
Feed Service updates group/event posts in the feed for members/attendees.
Group/Event Service stores data in the Group/Event Database.
10. Push Notifications
Flow: Push notifications are sent for real-time updates (likes, comments, messages, friend requests).
Data Flow:
Notification triggered (e.g., a new like or message).
Notification Service identifies recipient of the notification.
Notification is pushed to the frontend (mobile/web) using push notification services (e.g., Firebase Cloud Messaging, Apple Push Notification Service).
Frontend receives the notification and displays it in real time.
These data flows represent various interactions and processes within a typical social network architecture, where different services collaborate to provide a seamless experience for users.
High level Database Entity Diagram
erDiagram
Users ||--o{ Posts : creates
Users ||--o{ Comments : writes
Users ||--o{ Likes : gives
Users ||--o{ Messages : sends
Users ||--o{ Friendships : "participates in"
Users ||--o{ Notifications : receives
Users ||--o{ Media : uploads
Users {
uuid id PK
string email
string password_hash
string full_name
string profile_pic_url
datetime created_at
boolean is_verified
json settings
string oauth_provider
string oauth_id
}
Posts {
uuid id PK
uuid user_id FK
string content
datetime created_at
array media_urls
json metadata
int view_count
boolean is_public
}
Comments {
uuid id PK
uuid post_id FK
uuid user_id FK
string content
datetime created_at
uuid parent_id FK
}
Likes {
uuid id PK
uuid user_id FK
uuid post_id FK
datetime created_at
string reaction_type
}
Messages {
uuid id PK
uuid sender_id FK
uuid receiver_id FK
string content
datetime sent_at
boolean is_read
array attachments
}
Friendships {
uuid id PK
uuid user_id1 FK
uuid user_id2 FK
string status
datetime created_at
datetime updated_at
}
Notifications {
uuid id PK
uuid user_id FK
string type
json payload
datetime created_at
boolean is_read
}
Media {
uuid id PK
uuid user_id FK
string url
string type
int size
string status
json metadata
datetime uploaded_at
}
Posts ||--o{ Comments : has
Posts ||--o{ Likes : receives
Posts ||--o{ Media : contains
Key aspects of the ERD:
Uses UUID for distributed system scalability
Implements soft deletion and timestamps for data tracking
Stores JSON metadata for flexibility
Includes OAuth integration fields
Uses array types for media and attachments
Maintains referential integrity with foreign keys
Search Engine of Social Network
graph TB
subgraph Client Layer
A[Web/Mobile Client]
B[Search UI Component]
end
subgraph API Layer
C[API Gateway]
D[Search Service]
E[Rate Limiter]
end
subgraph Search Core
F[Elasticsearch Cluster]
G[Search Query Builder]
H[Result Formatter]
I[Search Analytics]
end
subgraph Data Layer
J[MongoDB - Posts]
K[PostgreSQL - Users]
L[Redis Cache]
end
subgraph Indexing Pipeline
M[Data Change Detector]
N[Index Manager]
O[Document Processor]
end
A -->|Search Request| B
B -->|API Call| C
C -->|Forward| D
D -->|Rate Check| E
E -->|Query| G
G -->|Execute| F
F -->|Raw Results| H
H -->|Format| D
D -->|Cache| L
J -->|Changes| M
K -->|Changes| M
M -->|Notify| N
N -->|Process| O
O -->|Update| F
D -->|Log| I
I -->|Improve| G
classDef service fill:#f9f,stroke:#333
classDef database fill:#69b,stroke:#333
classDef pipeline fill:#ffb,stroke:#333
class D,G,H service
class F,J,K,L database
class M,N,O pipeline
The diagram shows the flow of data:
Search request starts at the Client Layer
Flows through the API Layer with rate limiting
Gets processed in the Search Core
Results are formatted and returned
Meanwhile, the Indexing Pipeline ensures data stays fresh
The arrows in the diagram show:
Solid lines: Direct communication paths
Data flow from databases to search indices
Analytics feedback loop for optimization
Caching mechanisms for performance
The color coding indicates: - Services (pink fill) - Databases (blue fill) - Pipeline components (yellow fill) Lets understand the diagram by breaking it down into its main layers and components:
Client Layer
Web/Mobile Client: Entry point for user interactions
Search UI Component: Handles search input, autocomplete, and result display
This layer manages user interactions and formats search requests before sending them to the API
API Layer
API Gateway: Central entry point for all API requests, handles authentication and routing
Search Service: Core service that orchestrates the search functionality
Rate Limiter: Prevents abuse by limiting the number of requests per user/time period
Search Core
Elasticsearch Cluster: Main search engine that indexes and searches data
Handles distributed search across multiple nodes
Maintains indices for users, posts, and other content