Column store databases have several advantages over traditional databases - most notably compression and faster seek. Column store seem to be the new fad for databases in the past few years, with HANA as the most obvious example, but Microsoft and Oracle (and others) following suite.

However, the idea of column store databases are not new:

TAXIR was the first application of a column-oriented database storage system ... in 1969


Why has it taken until the last 8 years for column databases to take off? Surely compression in database was hugely useful in the 1970's when hard drive storage was not as dirt cheap as it is now (and faster seek never hurts). Is there another development in the last decade that enabled column store databases?


By and large, I think the increase in the popularity of data warehousing is prompting the move to Columnstore indexes.

Columnstore indexes are geared toward increasing query performance for workloads that involve large amounts of data, typically found in data warehouse fact tables.

Columnstore indexes store data by column rather than by row. By storing data in columns rather than rows, the database can more precisely access the data it needs to answer a query rather than scanning and discarding unwanted data in rows.

For wide tables, such as those commonly found in data warehouses, Column Store Indexes come in handy as you essentially reduce the amount and size of data needed to be accessed for any given query.

Check out some of these links for more information and examples:

Understanding the SQL Server Columnstore Index

Column-oriented DBMS

Columnstore Indexes in SQL Server 2012

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Your original premise, that "column store databases have several advantages over traditional databases", is overly general -- the statement is only true for certain workloads, specifically OLAP type, mostly read only, involving aggregation or window functions.

It is well known that volumes of data stored and processed by commercial users and government organizations have been growing exponentially in the last decade, and the types of workloads favoured by the column-organized storage engines, particularly business analytics and machine learning applications, where the benefits of column stores outweigh their disadvantages, have been growing more popular in the recent years.

These are the reasons that column-organized data stores have become more widely used only recently (relatively speaking).

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