Building real-time Bluesky analytics: ingesting 2.2M posts/day from the firehose
📰 Dev.to AI
Building a real-time analytics system for Bluesky's firehose using Python, FastAPI, and PostgreSQL
Action Steps
- Set up a WebSocket stream to ingest data from Bluesky's firehose
- Classify every post with AI using a suitable model
- Design a database schema to store and process ~2.2 million posts per day
- Implement data processing and analytics using Python, FastAPI, and PostgreSQL
Who Needs to Know This
Data scientists and software engineers can benefit from this system to analyze and process large amounts of data in real-time, informing business decisions and product development
Key Insight
💡 Real-time data processing and analytics can be achieved with a scalable architecture and suitable tools
Share This
💡 Process 2.2M posts/day from Bluesky's firehose with Python, FastAPI, and PostgreSQL
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