The JusDB Database Engineering Blog

Build blazing-fast analytics with ClickHouse columnar database. Learn MergeTree engine, data modeling, query optimization, and cluster deployment strategies.

Build a real-time analytics pipeline from PostgreSQL to ClickHouse using CDC — architecture, latency, and schema mapping

Use ClickHouse for sub-second analytics on billions of rows. Covers MergeTree table engine, LowCardinality types, AggregatingMergeTree materialized views, and MySQL ingestion.

ClickHouse MergeTree is why ClickHouse queries 1 billion rows in 0.3 seconds. Learn how parts, merges, and sparse indexes work, and how to choose the ORDER BY key, secondary indexes, and MergeTree variants.

ClickHouse Cloud is convenient but can cost 3-5x more than a well-tuned self-hosted cluster at scale. This breakdown shows exactly where the cost lines cross.

A detailed comparison of ClickHouse and BigQuery for analytical workloads — MergeTree engine vs Capacitor storage, self-hosted vs serverless cost models, query latency, real-time ingestion, and when to choose each.

Compare Snowflake, ClickHouse, and BigQuery on performance, cost, ecosystem, and real-world use cases