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Databases & messaging · #clickhouse
Keep only the latest version of duplicate ClickHouse event rows using ReplacingMergeTree and FINAL, without row-level UPDATE or DELETE.
TTL in ClickHouse is evaluated per-part during background merges, not by a cron job. Learn how to compile a 30-day drop policy, verify with system.ttl, and avoid common pitfalls.
ClickHouse’s TTL clause automatically purges old rows from MergeTree tables, eliminating manual cleanup scripts. Learn how to set it up, monitor it, and avoid common pitfalls in this concise guide.
MergeTree performance for time-series data depends on partitioning and compression choices made at CREATE TABLE. This post walks through a practical schema for HTTP logs, shows how to tier ZSTD and LZ4 codecs, and explains how to verify partition pruning with EXPLAIN.
Learn how to use ClickHouse ReplacingMergeTree for idempotent writes. This guide covers minimal design, the reality of eventual consistency, and how to verify deduplication.
Choosing the right MergeTree variant for ClickHouse time‑series workloads balances deduplication, aggregation, and write performance. This guide compares MergeTree, ReplacingMergeTree, SummingMergeTree, AggregatingMergeTree, and CollapsingMergeTree, explains trade‑offs, and shows a concrete example.
Guide to decide which ClickHouse table engine fits your deduplication needs, with trade‑offs and a ready‑to‑run DDL example.
Align ClickHouse MergeTree PARTITION BY and ORDER BY with query patterns and retention to enable partition pruning and index skipping for time-series analytics.
How ClickHouse Materialized Views pre‑aggregate data at ingest time with AggregatingMergeTree, and the operational trade‑offs engineers must weigh before adopting them for real‑time dashboards.