Finnhub Streaming Data Pipeline
Production-grade real-time analytics pipeline for financial market data using modern streaming architecture
Overview
A sophisticated real-time analytics pipeline for processing financial market data from Finnhub’s WebSocket API. The system demonstrates a highly scalable, cloud-native architecture focused on low latency and high availability.
Technical Details
Data Ingestion Layer
- Python-based Kafka producer
- WebSocket API integration
- Avro message serialization
- Schema registry management
- Docker containerization
Stream Processing
- Spark Structured Streaming
- Real-time data transformations
- Window-based aggregations
- Scala implementation
- Kubernetes deployment
Storage and Analytics
- Cassandra NoSQL database
- Optimized schema design
- Real-time Grafana dashboards
- Sub-second data refresh
- High-throughput writes
Infrastructure
- Kubernetes orchestration
- Terraform IaC
- Multi-cloud compatibility
- Monitoring and logging
- High availability setup
Implementation Results
The system achieved significant milestones:
- Sub-second data processing latency
- Highly available distributed system
- Cloud-agnostic deployment
- Scalable data processing
- Real-time analytics capabilities
Technical Stack
- Apache Kafka for streaming
- Spark for processing
- Cassandra for storage
- Kubernetes for orchestration
- Terraform for infrastructure
- Python and Scala for development
- Grafana for visualization
- Docker for containerization