---
type: architecture-decision
title: ClickHouse reporting and analytics service for a B2B payments platform
domain: fintech
services: [backend-platform, quality-knowledge]
skills: [System Design, Distributed Systems, SQL, Performance Optimization, Event-Driven Architecture]
technologies: [ClickHouse, Kafka, Go, PostgreSQL]
problem: A B2B payments platform needed aggregation, analytics, and metrics over growing operational data; running analytical queries on the transactional PostgreSQL database was slow and put the payment path at risk.
approach: Architected a dedicated reporting service on ClickHouse with event ingestion via Kafka, designed pre-aggregation schemas for the query patterns the business actually needed, and tuned both PostgreSQL and ClickHouse (partitioning, connection pooling) for analytical workloads.
result: A reporting system that serves analytics and metrics without touching the transactional path — cutting report generation from ~30s on PostgreSQL to under 2s on ClickHouse, and staying fast as volume grew past 1M+ events/day.
evidence: Described in work history (Korvax, 2022–present); architecture walkthrough available in a call.
public_links: []
available_for: private walkthrough
language: en
canonical: https://asmanmalikov.com/en/proof/clickhouse-reporting/
---

# ClickHouse reporting and analytics service for a B2B payments platform

- **Problem:** A B2B payments platform needed aggregation, analytics, and metrics over growing operational data; running analytical queries on the transactional PostgreSQL database was slow and put the payment path at risk.
- **Approach:** Architected a dedicated reporting service on ClickHouse with event ingestion via Kafka, designed pre-aggregation schemas for the query patterns the business actually needed, and tuned both PostgreSQL and ClickHouse (partitioning, connection pooling) for analytical workloads.
- **Result:** A reporting system that serves analytics and metrics without touching the transactional path — cutting report generation from ~30s on PostgreSQL to under 2s on ClickHouse, and staying fast as volume grew past 1M+ events/day.
- **Evidence:** Described in work history (Korvax, 2022–present); architecture walkthrough available in a call.