ClickHouse
ClickHouse Performance Observability: 9 Proven Signals We Trust in 26.9
ClickHouse performance observability on ClickHouse 26.9: nine system tables and endpoints, tested SQL, and a real Code 241 incident traced to one function.
ClickHouse Performance
ChistaDATA Performance
ClickHouse Performance Audit: 8 Best Tips for 26.8 LTS
ClickHouse performance audit tips for 26.8 LTS with real lab output: rank query shapes in system.query_log, measure cold past the query condition cache, read EXPLAIN ANALYZE and EXPLAIN WHATIF, and audit codecs per block.
ClickHouse
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
ClickHouse Merge Performance: Diagnosing Too Many Parts, Slow Merges, and Stuck Mutations
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
Scaling ClickHouse Horizontally: Sharding, Distributed Tables, and Parallel Replicas
Horizontal scale is where most ClickHouse fleets accumulate their deepest operational debt. ClickHouse sharding gets introduced months before the workload justifies it, and once a sharding key is baked into a production Distributed table, unwinding […]
ClickHouse
ClickHouse MergeTree Optimization: Sort Keys, Partitioning, Skip Indexes, and Projections
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
ClickHouse IOPS Troubleshooting: A Complete Guide to Diagnosing and Fixing Disk I/O Bottlenecks
NEEDS FEATURED IMAGE. ClickHouse IOPS troubleshooting guide for DBAs and SREs: diagnose disk I/O bottlenecks with ClickHouse system tables, verify at the OS layer with iostat and pidstat, fix merge storms and part explosion, tune caches, tier storage, and monitor IOPS continuously with Prometheus and Grafana.
ClickHouse Sharding
ClickHouse Shard Contention Troubleshooting: A Complete Guide
ClickHouse shard contention is one of the most frustrating performance problems a distributed database team can face. When a cluster scales out to dozens or hundreds of nodes, the promise of linear scalability quietly breaks […]
Analytics
ClickHouse Retail Analytics with Python: A Real-Time Reference Architecture
Retail runs on events. Every scanned item at a point-of-sale terminal, every product view on an e-commerce storefront, every abandoned cart, price change, and inventory adjustment is a discrete signal generated at high velocity. Modern […]
ClickHouse
20 Things You Should Not Do With ClickHouse Which Will Destroy ClickHouse Performance
ClickHouse is one of the fastest open source columnar databases for real-time analytics, and it powers observability platforms, product analytics, and large-scale reporting workloads across the industry. Yet raw speed can be deceptive. Many teams […]