---
title: "How ClickStack makes ClickHouse faster for observability"
description: "ClickHouse delivers high performance for telemetry data, but unoptimized queries on high-cardinality observability workloads can bypass pruning, inflate intermediate state, and exhaust cluster resources. ClickStack addresses this challenge by embedding engine-specific optimization best practices directly into how queries are generated, structured, and executed. For search workflows, the platform executes progressive queries across bounded time windows using optimize_read_in_order to return initial rows rapidly without scanning entire historical ranges. ClickStack also segments large chart aggregations into parallel bucket-aligned queries, automatically redirects map attribute filters to pre-materialized columns, and extends lazy materialization thresholds to minimize runtime input-output overhead. These query formulation strategies are being packaged into specialized analytical endpoints to power notebooks and external tools without requiring manual SQL tuning or exposing raw database interfaces."
---

# How ClickStack makes ClickHouse faster for observability

[Clickhouse](https://yomu.fyi/company/clickhouse) · Mike Shi · Mar 18, 2026

**Type:** Problem & solution

## Summary

ClickHouse delivers high performance for telemetry data, but unoptimized queries on high-cardinality observability workloads can bypass pruning, inflate intermediate state, and exhaust cluster resources. ClickStack addresses this challenge by embedding engine-specific optimization best practices directly into how queries are generated, structured, and executed. For search workflows, the platform executes progressive queries across bounded time windows using optimize\_read\_in\_order to return initial rows rapidly without scanning entire historical ranges. ClickStack also segments large chart aggregations into parallel bucket-aligned queries, automatically redirects map attribute filters to pre-materialized columns, and extends lazy materialization thresholds to minimize runtime input-output overhead. These query formulation strategies are being packaged into specialized analytical endpoints to power notebooks and external tools without requiring manual SQL tuning or exposing raw database interfaces.

## Context

Observability workloads on ClickHouse often involve high cardinality and semi-structured telemetry data. Naive or poorly shaped SQL queries can bypass partition pruning, trigger expensive runtime map extractions, inflate intermediate state, and waste cluster CPU and memory during large-scale scans and aggregations.

## Approach / What changed

ClickStack integrates query construction directly with ClickHouse internals to automatically optimize execution patterns. It implements progressive time-window searching aligned with table ordering keys, executes granularity-aligned parallel chunked queries for charts, transparently rewrites map filters to ingest-time materialized columns, and raises the query\_plan\_max\_limit\_for\_lazy\_materialization threshold to defer column loading across larger result sets.

## Takeaways

- Progressive searching across expanding time windows combined with optimize\_read\_in\_order delivers fast initial search results without requiring full table scans or global sorts over large date ranges.
- Chunking long-range chart queries into granularity-aligned time windows enables parallel execution and progressive client rendering while preventing cluster resource saturation and timeouts.
- Extracting semi-structured Map attributes into materialized columns at ingest time allows ClickStack to transparently rewrite filters to physical columns, improving compression and pruning.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Observability](https://yomu.fyi/topic/observability), [Performance](https://yomu.fyi/topic/performance), [Search](https://yomu.fyi/topic/search)

- Source: [Clickhouse](https://clickhouse.com/blog/clickstack-faster-observability)
- Source URL: https://clickhouse.com/blog/clickstack-faster-observability
- Ingested by Yomu: 2026-08-28T01:22:38.732Z

[Read original post](https://clickhouse.com/blog/clickstack-faster-observability)