---
title: "The end-to-end cost-performance of real-time analytics: Snowflake vs. ClickHouse Cloud"
description: "CostBench compares Snowflake and ClickHouse Cloud as end-to-end real-time analytics systems rather than measuring reads on a static, prepared dataset. It evaluates continuous ingest, raw-data organization, pre-aggregation freshness, and continuous query serving while background work continues, testing Snowflake’s standard-table and Interactive Tables paths alongside ClickHouse. The benchmark is designed around fresh data becoming query-ready as it arrives and distinguishes sustained real-time ingest from bulk loading or backfill. In the reported results, ClickHouse achieved 969× better cost-performance than Snowflake’s standard materialized-view setup and 180× better than its Interactive Tables setup; among the tested paths, only ClickHouse incremental materialized views kept pre-aggregations continuously synchronized without lag."
---

# The end-to-end cost-performance of real-time analytics: Snowflake vs. ClickHouse Cloud

[Clickhouse](https://yomu.fyi/company/clickhouse) · Jun 23, 2026

**Type:** Benchmark

## Summary

CostBench compares Snowflake and ClickHouse Cloud as end-to-end real-time analytics systems rather than measuring reads on a static, prepared dataset. It evaluates continuous ingest, raw-data organization, pre-aggregation freshness, and continuous query serving while background work continues, testing Snowflake’s standard-table and Interactive Tables paths alongside ClickHouse. The benchmark is designed around fresh data becoming query-ready as it arrives and distinguishes sustained real-time ingest from bulk loading or backfill. In the reported results, ClickHouse achieved 969× better cost-performance than Snowflake’s standard materialized-view setup and 180× better than its Interactive Tables setup; among the tested paths, only ClickHouse incremental materialized views kept pre-aggregations continuously synchronized without lag.

## Context

The post argues that static-dataset read benchmarks do not capture the cost or latency of making fresh data query-ready, maintaining derived data, preserving freshness, and serving queries while ingest and maintenance continue. It presents real-time analytics as a full path from continuously arriving data to continuously served answers.

## Approach / What changed

CostBench measures continuous ingest, raw-data organization, pre-aggregation maintenance and freshness, and query serving together. The comparison tests ClickHouse against Snowflake’s broadly available standard-table setup and newer Interactive Tables setup, using a workload in which fresh data must become query-ready as it arrives rather than a bulk-load or backfill process.

## Takeaways

- CostBench measures the running cost and latency of ingest, query-ready data maintenance, derived-data freshness, and query execution together instead of isolating static reads.
- The comparison includes Snowflake standard tables and Interactive Tables, while ClickHouse uses query-ready ingest and incremental materialized views for continuously maintained pre-aggregations.
- ClickHouse delivered 969× better cost-performance than Snowflake’s standard materialized-view setup and 180× better than Snowflake’s Interactive Tables setup in the expanded benchmark.

**Tags:** [Data Pipelines](https://yomu.fyi/topic/data-pipelines), [Performance](https://yomu.fyi/topic/performance), [Streaming](https://yomu.fyi/topic/streaming)

- Source: [Clickhouse](https://clickhouse.com/blog/real-time-analytics-cost-performance-snowflake-vs-clickhouse)
- Source URL: https://clickhouse.com/blog/real-time-analytics-cost-performance-snowflake-vs-clickhouse
- Ingested by Yomu: 2026-08-29T01:36:12.908Z

[Read original post](https://clickhouse.com/blog/real-time-analytics-cost-performance-snowflake-vs-clickhouse)