Built an analytics platform processing 500K+ events/second with sub-second query latency for SaaS analytics provider
<1 second
Query Latency
Achieved sub-second latency for 99th percentile queries
500K+ EPS
Event Throughput
Handles 500K events per second with automatic scaling
60%
Cost Reduction
Infrastructure costs down 60% through optimization
12x
Storage Efficiency
12x compression ratio through columnar format
A B2B analytics company served hundreds of enterprise customers, each generating millions of events daily. Their existing stack couldn't keep up with event volume, leading to stale data and slow queries. Customers expected real-time analytics, not 10+ minute delays.
We redesigned the entire data infrastructure with focus on real-time processing: - Event streaming architecture using Kafka with 500K+ EPS throughput - Real-time aggregation using Flink for sub-second latency queries - Efficient time-series storage with columnar format and aggressive compression - Multi-tenant data partitioning with query isolation
The analytics company had grown rapidly, acquiring many enterprise customers, but their data infrastructure hadn't scaled accordingly. Their pipeline processed events with significant latency, making it impossible to offer "real-time" analytics—a critical selling point.
The legacy system had multiple bottlenecks:
We designed a modern streaming-first architecture:
**Ingestion Layer**
**Processing Layer**
**Storage Layer**
The migration happened in phases: 1. Deployed new infrastructure in parallel (3 months) 2. Began dual-writing to old and new systems (2 months) 3. Gradual traffic migration with automatic failover (3 months) 4. Decommissioned legacy system (3 months)
Each customer was migrated individually with their data fully validated before switching their queries.
- Query latency dropped from 5-10 minutes to <1 second
The company was able to use real-time analytics as a key differentiator, winning major enterprise customers who specifically required sub-second latency.
Analytics SaaS Company
Analytics & Business Intelligence
Query Latency
Event Throughput
Cost Reduction
Storage Efficiency