Project Name
StarRocks Replaced Separate OLTP and OLAP: 200K TPS Fintech Gets 500ms Fraud Detection
A fintech platform processing 200K+ transactions per second across digital banking, UPI, and card networks needed real-time visibility for fraud detection, customer analytics, and regulatory compliance. Separate OLTP and OLAP systems delayed fraud detection. Complex ETL pipelines and vertical scaling costs limited efficiency. Compliance dashboards ran on stale batch data. Applying its AI-First approach, Ksolves built a unified real-time analytics platform on StarRocks with Kafka and Flink ingestion, delivering sub-2-second queries across 2.5 PB+ and 500ms fraud alert response times at 99.99% availability.
- High-Frequency Transactions at 200K+ TPS: No existing system could support concurrent analytical queries at 200K+ TPS without degrading transactional performance.
- Separate OLTP and OLAP Systems Delaying Fraud Detection: The gap between transaction occurrence and analytical visibility widened the fraud detection window.
- Complex ETL Pipelines: Multiple pipelines bridging transactional and analytical systems added lag, operational complexity, and maintenance overhead.
- Scaling Costs Unsustainable: Vertical scaling of existing infrastructure reached practical limits with no cost-efficient horizontal scaling path.
- No Real-Time Compliance Dashboards: Regulatory teams required live transaction dashboards. Batch-based reporting introduced unacceptable lag.
- Ad-Hoc SQL on Live Data Degraded Operations: Running analytical queries on the OLTP system impacted transactional processing performance.
Ksolves implemented a unified real-time data architecture using Kafka and Flink for stream ingestion and transformation into StarRocks as the Unified Analytical Warehouse. The governing principle: one platform for all workloads - fraud detection, compliance reporting, customer analytics, and ad-hoc SQL on live data without separate systems or pipeline duplication.
- Kafka + Flink Ingestion Pipeline: Kafka ingests 200K+ TPS from digital banking, UPI, and card networks. Flink handles real-time transformation and routing before writing to StarRocks, decoupling upstream systems from the analytical layer.
- StarRocks Unified Analytical Warehouse: 3 FE nodes for query routing, 16 CN nodes for compute and storage. 5TB+ ingested daily across 2.5 PB+ at 99.99% availability with zero data loss.
- Materialized Views and Rollup Tables: Pre-computed fraud analytics and performance monitoring summaries update automatically as new data lands - 500ms fraud alert response, no full-table scans.
- Apache Superset Dashboards: 80+ concurrent users run real-time compliance and fraud investigation queries on live StarRocks data without impacting operational performance.
- Prometheus + Grafana Monitoring: Cluster health, Kafka consumer lag, and Flink job performance monitored in real time with configurable alerting.
Technology Stack
| Category | Technology |
|---|---|
| Streaming | Apache Kafka + Apache Flink |
| Analytics Warehouse | StarRocks (3 FE + 16 CN Nodes) |
| Aggregation | Materialized Views + Rollup Tables |
| Visualization | Apache Superset |
| Monitoring | Prometheus + Grafana |
- Sub-2-Second Query Latency Across 2.5 PB+: StarRocks delivers end-to-end query latency under 2 seconds across the full transaction history. Fraud analytics and compliance queries return in real time.
- 500ms Average Fraud Alert Response: Materialized Views enable 500ms fraud alert response. Fraud detection window reduced from minutes to milliseconds.
- 40% Infrastructure Cost Reduction: Unifying batch and streaming on a single StarRocks platform eliminated separate OLTP and OLAP systems, cutting infrastructure cost 40%.
- 99.99% Uptime, Zero Data Loss: StarRocks maintained 99.99% system availability across 5TB+ daily ingestion. Zero data loss events recorded.
- Ad-Hoc SQL on Live Data Without Operational Impact: Data teams run fraud investigation and customer behaviour queries directly on StarRocks without degrading transactional performance.
- Real-Time Compliance Dashboards for 80+ Users: Compliance teams access live transaction dashboards via Superset with no batch lag.
“We were running separate systems with ETL pipelines holding everything together. Fraud detection lagged. Compliance reports were always stale. StarRocks unified everything – we detect fraud in 500 milliseconds, run compliance dashboards on live data, and pay 40% less than we did with two separate systems.”
– Head of Data Engineering / CTO.
A fintech platform delayed by separate OLTP and OLAP systems, complex ETL pipelines, and stale compliance reports was transformed through Ksolves Big Data Services. StarRocks unified all analytical workloads on one platform. Kafka and Flink deliver 5TB+ daily at 200K+ TPS. Sub-2-second query latency across 2.5 PB+. Fraud alerts in 500ms. Compliance dashboards live. Infrastructure cost down 40%. 99.99% uptime. Zero data loss. 80+ concurrent users on real-time data.
Still Running Separate OLTP and OLAP Systems While Fraud Events Widen Their Detection Window?
