Columnar Database

A columnar database has risen in popularity the last few years, and has been especially popular within the business intelligence and analytics world. We’ll take a look at some of the advantages of using this type of database vs. the standard row-oriented databases used in other applications.

For many years row-based databases were the standard, especially for transactional and OLTP type work. These types of technologies tend to work well with rapid inserts but not so much with accessing data, especially large amounts like may be needed for reporting and BI purposes. A columnar database makes these types of queries faster. Most queries usually only work with a couple of attributes, or dimensions, but may have a lot of row data. By storing data in columns it can more easily retrieve data with massive amounts of rows quickly. In addition, these datasets can often also be compressed many times more efficiently than the equivalent row based technologies. As BI implementers realized the power of this type of database, many data warehousing builds started using these types of databases.

Some of the larger database companies have realized the value of have this type of solution in their portfolio, and so they have started acquiring many of these technologies. Some of the bigger purchases were HP buying Vertica and SAP buying Sybase, with its Sybase IQ product. Teradata and EMC also acquired Aster Data and Greenplum, respectively. All of these occurred within about a year in 2010-2011. IBM and Oracle, seem to be developing more of the compatibility in-house. Oracle 11g supports columnar storage.

Vendors looking at big data such as 1010Data also use this technology, and I expect their market share will grow. I would expect companies like IBM to make their own forays into this space, either by acquisition or developing in-house. SQL Server 2012 for example, now has support for columnar storage.

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