ClickHouse Performance Archives

Setting up Alerts in ClickHouse for Performance Troubleshooting

Setting Up Alerts: Detecting ClickHouse Performance Degradation Before It Impacts Users Proactive alerting is a critical operational practice that prevents incidents by identifying performance degradation before it affects end users 4. This comprehensive guide demonstrates […]

ClickHouse Storage Tiering Best Practices: Moving Data Between Hot and Cold Storage with TTL

ChistaDATA Inc.

ClickHouse Storage Tiering Best Practices: Moving Data Between Hot and Cold Storage with TTL Efficient data management is critical for modern analytical databases, especially when dealing with large volumes of time-series or event-driven data. ClickHouse, […]

Overview of Vectorized Query Processing in ClickHouse

Troubleshooting Disk Space in ClickHouse

ChistaDATA Inc.

Troubleshooting Disk Space Issues: Managing ClickHouse Log Tables ClickHouse is a high-performance, columnar database management system optimized for real-time analytical workloads. While its speed and scalability make it ideal for large-scale data processing, one common […]

ClickHouse Search: Manticore Full Text Search with Plain Index

Essential ClickHouse Metrics

ChistaDATA Inc.

Essential ClickHouse Metrics: What to Monitor for Optimal Performance ClickHouse, the high-performance columnar database management system, exposes over 1,000 metrics for monitoring and observability 5. With such an extensive array of available metrics, selecting the […]

ClickHouse Search: Case-sensitive Searches with UPPER & LOWER Functions

Boosting Materialized View Performance

ChistaDATA Inc.

Aggregation States: Boosting Materialized View Performance by 10x in ClickHouse ClickHouse has long been celebrated for its lightning-fast analytical query performance, especially when handling massive datasets in real time. One of the most powerful features […]

ClickHouse Performance: Estimated & Actual Row Counts in Execution Plans

PREWHERE vs WHERE in ClickHouse Queries

ChistaDATA Inc.

PREWHERE vs WHERE: When and How to Optimize Your ClickHouse Queries Introduction Query performance in ClickHouse often hinges on how efficiently you filter data. While most SQL users are familiar with the WHERE clause, ClickHouse […]

Tuning index_granularity for ClickHouse Performance

Understanding ClickHouse Wait Events

ChistaDATA Inc.

Understanding ClickHouse Wait Events: A Comprehensive Troubleshooting Guide Introduction Wait events in ClickHouse reveal where query execution slows down—whether from disk bottlenecks, lock contention, CPU saturation, or network latency. Mastering these signals empowers you to […]

Using EXPLAIN to Determine JOIN Order in ClickHouse Query Execution Plan

Reduce Query Memory Usage in ClickHouse

ChistaDATA Inc.

How to Reduce Query Memory Usage in ClickHouse: Troubleshooting Memory Limit Exceeded Errors Memory limit exceeded errors are among the most common challenges ClickHouse users face when running complex analytical queries. Whether you’re performing large […]

Troubleshooting Underutilized ClickHouse Index

Unlock Blistering Query Speed with ClickHouse LowCardinality

ChistaDATA Inc.

Unlock Blistering Query Speed with ClickHouse LowCardinality: A ChistaDATA Guide ClickHouse is famous for raw speed, but some of its most powerful tools remain under-documented. Among them, the LowCardinality data type is arguably the simplest […]

Partitioning in ClickHouse

ChistaDATA Inc.

Mastering ClickHouse Partitioning for Optimal Query Speed Summary ClickHouse Partitioning is one of the fastest ways to boost query speed and simplify data retention in ClickHouse. By grouping rows into logical segments—usually by month, day, […]

* Everything changes over time – Our blogs/posts and comments changes over time, That’s how it should be! Whatever we comment from ChistaDATA Inc. Teams (including Shiv Iyer) and other stakeholders or guest bloggers posted here are never permanent, These things worked for us. But, there is no guarantee they will work for you too, When using the recommendations from ChistaDATA or MinervaDB or MinervaSQL or any other online resources / Google, You must test the advice before applying them to your production systems, and always invest for a robust Database DR solution, Thank you for understanding.

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