Case Study
Real-time Analytics Platform
Built a high-performance analytics dashboard for a B2B SaaS company processing high-frequency event streams.
Full Cycle
Timeline
Core Engineering
Team Size
Delivered a low-latency, modular analytics foundation that gives clients real-time telemetry and sub-second querying without infrastructure bottlenecks.
Impact
The Problem
Customers couldn't see real-time data due to slow queries (5+ seconds) and poor UI performance. The business was losing deals to competitors with faster analytics.
Our Solution
We redesigned the entire data pipeline: implemented event streaming with Apache Kafka, added Redis caching layer, optimized database queries through strategic indexing and table partitioning, and rebuilt the frontend with React for better performance.
The Challenge
What made this project complex
The platform needed to maintain sub-second query responses under heavy real-time data ingestion. The original architecture used a single PostgreSQL instance with no caching or query optimization.
Results & Impact
Measurable improvements
Query Architecture
Sub-Second
Optimized Indexing
Event Pipeline
Streaming
Kafka & Redis
UI Updates
Real-time
WebSocket
Data Consistency
ACID
PostgreSQL
What We Delivered
Query latency reduced from multi-second delays to sub-second responses
System architected to handle high-concurrency event streams reliably
Optimized compute footprint through database indexing and Redis caching
Real-time live streaming dashboards powered by bidirectional WebSockets
Modular frontend state architecture with predictable data caching
Technology Stack
Tools and frameworks used
- React
- Node.js
- PostgreSQL
- Apache Kafka
- Redis
- WebSocket
- AWS
- Docker