Columnar Storage

Columnar storage is a way of laying data on disk by column rather than by row. A traditional row store keeps all the fields of one record together, which is ideal for reading or updating a single row. A column store keeps all values of one column together, which is ideal for scanning one or two columns across millions of rows — exactly what analytics queries do. Why it matters to SaaS builders: if your queries look like "sum revenue by month across the whole table", columnar formats are dramatically faster and cheaper. Because a column holds values of the same type, it compresses extremely well, and the engine only reads the columns you actually select. Formats like Parquet and ORC, and warehouses like BigQuery, Snowflake, Redshift, and ClickHouse, are all columnar. Practical note: columnar shines for analytical (OLAP) workloads, not transactional (OLTP) ones. Single-row inserts and point lookups are comparatively slow, so keep your operational database row-based and move data into a columnar store for reporting.