Architecting Real-Time Blockchain Intelligence with Apache Beam and Apache Kafka

At TRM Labs, we manage petabyte-scale data from over 30 blockchains to deliver customer-facing analytics. Our platform processes high-throughput data to extract actionable intelligence for critical decision-making.

In this session, we will discuss how Apache Beam underpins our architecture by integrating with Apache Kafka for robust data ingestion and deploying on Google Cloud Dataflow to ensure scalability and fault tolerance. We will also delve into the complexities of handling massive volumes of blockchain data—peaking at up to one million events per second—in real time and computing complex metrics.

Key Takeaways: • Designing and scaling a real-time streaming data platform to meet the rigorous demands of petabyte-scale blockchain data. • Employing Apache Kafka for reliable, high-throughput data ingestion, with practical insights from networks such as BSC, Ethereum, and Tron. • Leveraging Apache Beam and Google Cloud Dataflow for scalable and flexible data processing and enrichment. • Ensuring exactly-once semantics for transactional data. • Optimizing high-throughput writes by fine-tuning the JDBC protocol at the TCP layer. • Implementing best practices for performance, monitoring, maintenance, and security in a high-stakes, real-time streaming environment.