ClickHouse Cloud Crushes Cloud Data Warehouse Costs

The Cost Performance Showdown

The article provides a compelling cost-performance comparison of major cloud data warehouses. The key insight is ClickHouse Cloud's superior performance across various data scales, particularly at 100B and 1T rows. This is noteworthy because it challenges the established dominance of other vendors like Snowflake and Databricks, highlighting significant cost savings for large-scale analytical workloads. The methodology, Bench2Cost, is innovative for its use of real-world compute pricing models, ensuring accurate and verifiable comparisons. However, the study has limitations. It focuses solely on compute costs and ignores storage costs, which, while mentioned, might be a factor for some workloads, especially those with very large datasets. Also, the benchmark is based on a specific workload (ClickBench) and may not fully represent the performance across all types of analytical queries. Finally, the article's focus on cost-performance may overlook other factors like ecosystem, ease of use, and specific feature sets that could be crucial for certain users.

This article benefits data engineers, data scientists, and anyone managing large datasets in the cloud. It provides a data-driven basis for making informed decisions about cloud data warehouse selection. It has significant technical implications, particularly for organizations seeking cost optimization. The findings suggest that ClickHouse Cloud is a strong contender for high-performance, cost-effective data warehousing. Compared to existing solutions, the article provides a concrete comparison based on real-world pricing which is a significant value add. It suggests that users should re-evaluate their current cloud data warehouse choices, especially if they are seeing high compute costs and have large datasets.

Key Points

• ClickHouse Cloud offers significantly better cost-performance than Snowflake, Databricks, BigQuery, and Redshift, especially at larger data scales (100B and 1T rows).
• The study uses a transparent and reproducible benchmarking methodology (Bench2Cost), applying actual compute pricing to the analysis.
• The article's interactive benchmark explorer allows users to explore the data and compare different configurations.
• The analysis focuses on compute cost and ignores storage costs, which are considered less significant in comparison.

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📖 Source: 主要5大クラウドデータウェアハウスのコストパフォーマンス比較