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Using ClickHouse to scale an events engine
Open Source Metering and Usage Based Billing API ⭐️ Consumption tracking, Subscription management, Pricing iterations, Payment orchestration & Revenue analytics - getlago/lago
Well, Postgres was designed to be strictly atomic and consistent; two properties that require for data to be fully ingested before any query that might process them is run. This creates a problem for tables where entries are ingested in the millions per minutes (e.g. billable events, especially those for infrastructure services like managed servers). ClickHouse has three notable features that make it an analytics powerhouse—(i) dynamic materialized views, (ii) specialized engines, and (iii) vectorized query execution.
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