Fri, 2016-04-29 08:22Nishant Vyas
Relational databases store data in rows because a typical SQL query looks for multiple fields within a record. For example, if you ask for name, zip code and email address of all your customers in New York, the result is presented in rows, with each row containing several fields from a single record. Row structures are also well optimized to handle a lot of inserts and updates.
But analytic queries are better handled with a column structure because they are more likely to go deep on a column of data, most queries relate only to a tiny subset of all the available columns and they’re also mostly read-only. For example, retrieving daily sales data for all your stores in California for the past two years is a columnar operation because it cuts across many records to retrieve data from a specific field. A typical ad-hoc aggregation query doesn’t care about most fields, just the trends in one …
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