Photogram: Your
Real-World
Social Media
Data Playground
Photogram is a ready-to-use synthetic dataset that mimics the experience of a real image-sharing platform. Ideal for recommendation engines, feed algorithm testing, content ranking, and user engagement analysis.
Overview
Photogram is a realistic synthetic dataset that mirrors how modern image-sharing platforms work. It captures everything from users, posts, likes, and comments to hashtags and timelines — making it perfect for building, testing, or analyzing social media features. Whether you're training recommendation systems, experimenting with content feeds, or simulating user behavior, Photogram gives you a practical, data-rich playground.
Ideal for developers, analysts, and students alike, Photogram helps validate backend features, model user engagement, and even test moderation systems. Its detailed, time-stamped records and relational structure make it great for honing SQL and data modeling skills, building dashboards, or studying how content goes viral.
Full Social Media Lifecycle
Simulates a complete image-sharing experience, including user onboarding, post creation, likes, comments, follower interactions, and story management.
Built for Development & Testing
Excellent for building and testing recommendation systems, bot detection models, content ranking algorithms, and engagement prediction pipelines.
Backend Feature Testing
Useful for developers working on feed logic, follower management, notification triggers, direct messaging, and moderation flows.
Rich Engagement Data
Supports use cases in user engagement analysis, follower growth modeling, retention research, and promotional content impact studies.
Analytics & Research
Suitable for SQL practice, ETL development, trend visualization, time-series analysis, and A/B testing simulations on social content.
How it Works
AI-Generated & Fully Synthetic
The Photogram dataset is generated using advanced AI agents, creating a realistic yet entirely synthetic representation of social media interactions with zero real-world or personally identifiable data.
Realistic Simulation with Privacy
It simulates user accounts, photo uploads, likes, comments, follower interactions, and tagging — all informed by publicly documented social media trends and app usage statistics.
High-Quality & Safe for Use
Built using insights from global social media platforms and public data patterns, the dataset delivers structured, high-quality data suitable for recommendation systems, analytics dashboards, and machine learning model training.
Dataset Schema
A comprehensive relational model representing a modern social media photo-sharing platform engineered for deep analysis and complex querying.
Users
Stores user credentials and profile details including bio, gender, and profile picture.
Posts
Stores user-generated image posts including URLs, captions, locations, and the user who posted.
Likes
Records which users liked which posts and when the interaction occurred.
Comments
Stores user comments on posts with timestamps and nested reply support.
Followers
Captures user-following relationships across the platform.
Stories
Stores time-limited content (stories) with images and user metadata.
Story Views
Logs who viewed which stories and when the views took place.
Saved Posts
Tracks posts saved by users for later viewing and reference.
Messages
Handles private direct messages between users including sender, receiver, and content.
Notifications
Logs notifications sent to users such as new followers, likes, and comments.
Hashtags
Maintains a catalog of hashtags used across the platform for content discovery.
Account Center
Manages user settings like social media links, login preferences, visibility, and subscriptions.
- CSV
- JSON
- Excel
- MySQL
- PostgreSQL
- SQL Server
- Snowflake