How do you make sense of Ethereum transactions as they happen?
Ethereum processes 1M+ transactions per day, and Uniswap alone handles $500M to $1B in daily volume — with thousands of swaps happening hourly. In that kind of flow, real-time analytics isn’t optional — it’s essential to understand market dynamics.
So I built a real-time analytics pipeline for Ethereum Uniswap transactions:
– Streams Uniswap swap events
– Ingests into ClickHouse, a lightning-fast OLAP database
– Visualized live in Grafana
– Fully deployed on Azure using Terraform and best practices
Whether you’re into data engineering, cloud infrastructure, or Web3 analytics, this project connects all three worlds.
Problem: blockchain data is huge — but hard to use in real time.
- Ethereum has massive transaction volume (1+ million tx/day)
- Swaps on Uniswap are high-value events ($500M–$1B daily)
- How do you monitor this live?
Solution: tracking Uniswap swaps in real time
- Stream Ethereum events using Kafka
- Ingest data into ClickHouse, a high-performance OLAP database
- Build a real-time Grafana dashboard
- Deploy to Azure following Cloud Design Patterns and best practices
The architecture deployed on Azure
- Event Hub: Kafka-compatible and fully managed message queue
- Container Apps: fast deployment for Producer, ClickHouse and Grafana
- User-assigned Identity for increased security between services
What I built for this project
- Dockerized Producer, Consumer (ie. ClickHouse database) & Grafana dashboard
- The Producer app is a python script that reads live blockchain events and sends them in batch to the Event Hub
- Infrastructure-as-Code with Terraform
Real-time data in a Grafana Dashboard
This dashboard allows to monitor in real time:
- Number of swaps per block
- Total ETH swapped and $ value per block
Main challenges & What I learned
- How to build a real-time event-driven architecture, how to authenticate and set up the Consumer to read events from the Event Hub
- How to deploy a multiple environment cloud architecture using Terraform modules, how to Don’t Repeat Yourself (DRY) using Terragrunt, how to automate using the GitOps framework
What’s next?
Streaming real-time blockchain data unlocks powerful on-chain insights:
- Understanding market behavior
- Identify emerging trends early
- Detect whales or suspicious activity
- Enable instant alerts and dashboards
- Build better strategies for trading bots