ClickHouse DBA Script Archives

ClickHouse Ingestion Performance: Batch Sizing, Async Inserts, and Kafka Pipelines

ClickHouse ingestion performance is decided long before the query planner ever touches your data. It is decided by how many parts your writers create per second, how much background merge work those parts generate, and […]

ClickHouse Merge Performance: Diagnosing Too Many Parts, Slow Merges, and Stuck Mutations

ChistaDATA Inc.

ClickHouse merge performance is the hinge on which every high-ingest MergeTree deployment turns. When background merges keep pace with inserts, part counts stay flat and SELECT latency stays predictable. When they fall behind, the failure […]

ClickHouse MergeTree Optimization: Sort Keys, Partitioning, Skip Indexes, and Projections

ChistaDATA Inc.

ClickHouse MergeTree optimization is the difference between a table that answers analytical queries in milliseconds and one that scans hundreds of gigabytes for every request. This guide is written for senior engineers who already understand […]

ClickHouse Query Performance Tuning: A Production Diagnostic Playbook

ChistaDATA Inc.

Effective ClickHouse query performance tuning is less about magic settings and more about a repeatable diagnostic loop: measure, read the plan, isolate the bottleneck, change one variable, and re-measure. This playbook is written for senior […]

ClickHouse Real-Time POS Analytics: Sub-Second Decisioning for QSR Enterprises

ChistaDATA Inc.

If you’ve spent any time working in QSR (Quick Service Restaurant) data infrastructure, you already know the problem. The need for ClickHouse real-time POS analytics has never been more urgent — millions of POS transactions […]

eBPF | ClickHouse Performance | ChistaDATA

Advanced eBPF-Based Performance Analysis for ClickHouse

ChistaDATA Inc.

Advanced eBPF-Based Performance Analysis for ClickHouse: Kernel-Level Observability Techniques eBPF (Extended Berkeley Packet Filter) delivers comprehensive, zero-overhead kernel-space observability for ClickHouse performance analysis. Through dynamic instrumentation of kernel tracepoints, kprobes, uprobes, and hardware performance monitoring […]

ClickHouse Performance Detective’s Toolkit

ChistaDATA Inc.

ClickHouse Performance Detective’s Toolkit: CLI Strategies for Common ClickHouse Bottlenecks When your ClickHouse database starts showing signs of performance degradation, the command-line interface becomes your most powerful diagnostic tool. Unlike traditional databases that rely heavily […]

ClickHouse Thread Contention and Troubleshooting

ChistaDATA Inc.

ClickHouse Thread Contention and Troubleshooting: A Comprehensive Guide ClickHouse has established itself as one of the most powerful open-source columnar database management systems designed for online analytical processing (OLAP). Its exceptional performance stems from a […]

Avoiding Costly Mistakes: Profile Events and Query Traces in a Single ClickHouse Query

ChistaDATA Inc.

Effortlessly Profile Events and Query Traces in a Single ClickHouse Query ClickHouse’s exceptional performance in analytical workloads comes with the challenge of understanding and optimizing complex query execution patterns. When queries don’t perform as expected, […]

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 […]

* 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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