Columnar storage

Storing each column together makes scanning one column across billions of rows fast and compresses very well, which is why warehouses use it. Fetching one full row is slower.

Where it shows up in real systems

  • Data warehouse

    Built for large analytical queries that take seconds, not for serving users. Placing it in a request path destroys latency; feed it asynchronously through a pipeline instead.

    In production: Snowflake, Google BigQuery, Amazon Redshift, ClickHouse, Databricks SQL

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