Twitter Sentiment ETL Pipeline with MongoDB & Postgres

This n8n workflow builds a complete ETL pipeline for social media monitoring: it collects Twitter posts, stores the raw data in MongoDB, runs sentiment analysis using Google Cloud Natural Language, and writes the processed results into Postgres for structured querying. Any posts flagged as significant trigger an instant Slack notification, keeping teams informed in real time. It's designed for social listening, brand monitoring, and research teams who need a reliable pipeline for cleaning, analyzing, and storing text data at scale.

Category: Database & Integration