Reference patterns, governed by how well they are sourced

Challenge

Analytics over internet-scale HTTP and security event traffic, served both internally and to millions of customers in-product.

Approach

Large ClickHouse deployment replacing earlier time-series infrastructure, with aggressive pre-aggregation for per-customer dashboards.

Outcomes

• · Internet-scale event ingest with interactive query latency
• · Customer-facing analytics served from the same platform as internal analysis
• · Substantially lower infrastructure footprint than the previous stack

Challenge

Operational analytics and observability across a large microservice estate with cost pressure on the incumbent tooling.

Approach

ClickHouse as the store for high-volume operational telemetry and real-time marketplace metrics.

Outcomes

• · Interactive queries over high-volume operational data
• · Reduced cost per GB of telemetry retained
• · Faster incident investigation for platform teams

Challenge

Marketplace abuse and fraud patterns spanning shoppers, customers and orders needed fast detection across large event volumes.

Approach

Event pipelines into ClickHouse to power near-real-time detection features and analyst investigation.

Outcomes

• · Detection and investigation on fresh data instead of batch cycles
• · Analysts able to pivot across full event history interactively

Challenge

Quantitative research over enormous tick and market data histories, where research iteration speed drives returns.

Approach

ClickHouse as the research data platform for time-series market data at trillions of rows.

Outcomes

• · Interactive access to full-history market data
• · Faster research iteration for quantitative teams
• · Cost-effective long retention of tick data

Challenge

Ultra-high-volume market data analytics where query latency directly constrains research throughput.

Approach

ClickHouse for time-series market data analysis alongside specialised in-house systems.

Outcomes

• · High-throughput ingest of market data
• · Low-latency analytical access for research and TCA

Challenge

A fraud-prevention vendor needing to serve real-time risk signals and customer-facing analytics to its own clients.

Approach

ClickHouse behind the product for event storage, feature aggregation and multi-tenant analytics.

Outcomes

• · Real-time risk signals served at product latency
• · Customer-facing analytics without per-query cost blowups

Challenge

A cloud-native card processor needing transparent, real-time transaction analytics for merchants and internal ops.

Approach

ClickHouse as the analytics layer over payment event streams and processor responses.

Outcomes

• · Real-time transaction visibility for customers
• · Operational insight into processor behaviour

Challenge

Authorisation-rate optimisation requires analysing every attempt, decline reason and retry across processors.

Approach

ClickHouse for high-volume authorisation event analytics powering routing and merchant reporting.

Outcomes

• · Fast detection of processor performance changes
• · Data-driven routing and retry decisions

Challenge

A regulated neobank needing real-time transaction monitoring, fraud detection and internal analytics.

Approach

ClickHouse for transaction and behavioural analytics, fed from operational systems and streams.

Outcomes

• · Faster transaction monitoring and fraud review
• · Analytics decoupled from operational databases

Challenge

Continental-scale marketplace and payments platform with enormous event volumes and real-time fraud requirements.

Approach

ClickHouse for large-scale real-time analytics across commerce and payment events.

Outcomes

• · Real-time analytics at continental marketplace scale
• · Fraud and payments teams working from fresh data

Challenge

Security telemetry from many managed endpoints, where SIEM-style pricing made full collection unaffordable.

Approach

ClickHouse as the security data lake supporting detection and analyst hunting.

Outcomes

• · More telemetry retained for longer
• · Faster analyst investigation across the estate

Challenge

Usage analytics across school districts, delivered to institutional customers with predictable cost.

Approach

ClickHouse serving multi-tenant usage analytics with pre-aggregated rollups.

Outcomes

• · District-facing analytics at interactive speed
• · Cost per tenant kept predictable as usage grew

Challenge

A behavioural analytics vendor serving interactive session analytics to enterprise customers at web scale.

Approach

ClickHouse as a core analytical engine for high-volume behavioural events.

Outcomes

• · Interactive analysis over very large behavioural datasets
• · Product performance decoupled from data growth

Challenge

Streaming quality-of-experience and audience analytics during large live events with extreme traffic spikes.

Approach

ClickHouse for real-time viewership and QoE metrics during live sport and entertainment.

Outcomes

• · Real-time visibility during peak live events
• · Operational decisions made during, not after, a broadcast

Challenge

Storing and querying LLM traces, prompts and evaluation results for many customer projects.

Approach

ClickHouse as the trace and analytics store behind an open-source LLM observability platform.

Outcomes

• · Trace analytics at product latency
• · Scalable multi-tenant retention of large text payloads

Challenge

Rapidly growing AI product needing usage, cost and quality analytics without building a data team first.

Approach

ClickHouse for product and LLM usage analytics feeding internal decisions and unit-economics tracking.

Outcomes

• · Fast product analytics at hypergrowth ingest rates
• · Per-feature cost attribution for AI spend

Challenge

Experiment and model telemetry from thousands of ML teams, queried interactively inside the product.

Approach

ClickHouse powering high-volume metric and trace analytics for the ML platform.

Outcomes

• · Interactive experiment analytics at scale
• · Sustainable cost as customer telemetry grew

Challenge

Player, economy and infrastructure telemetry across games with unpredictable growth.

Approach

ClickHouse for real-time game and platform analytics including abuse detection.

Outcomes

• · Real-time visibility into player economy and platform health
• · Lower analytics cost per player

Challenge

Delivering per-customer documentation analytics without operating a heavy data platform.

Approach

ClickHouse as the analytics backend for customer-facing documentation insights.

Outcomes

• · Customer-facing analytics shipped by a small team
• · Predictable cost as customers scaled

Challenge

Product usage analytics across a very large user base with a small engineering team.

Approach

ClickHouse replacing slower general-purpose analytics queries for product and usage insight.

Outcomes

• · Order-of-magnitude faster product analytics queries
• · Analytics load removed from the operational database