9 articles in this selection

2009/12/16

Columnar in-memory plugin for Excel. Similar to Microsoft PowerPivot.

2009/08/03

This is the first of a two-part series that will examine trends and market drivers in data warehousing and business intelligence for the second half of 2009 and, just as important, what IT directors, managers and executives should do about them.

2009/07/26

As the name implies, columnar databases are organized by column rather than row: that is, all instances of a single data element (say, Customer Name) are stored together so they can be accessed as a unit. This makes them particularly efficient at analytical queries, such as list selections, which often read a few data elements but need to see all instances of these elements. In contrast, a conventional relational database stores data by rows, so all information for a particular record (row) is immediately accessible. This makes sense for transactional queries, which typically concern one record at a time. Today's columnar systems combine the columnar structure with techniques including indexing, compression and parallelization. But the fundamental questions asked in evaluating these systems are the still the same....

2009/07/22

The paper, titled "A Comparison of Approaches to Large-Scale Data Analysis" is sure to stoke heated discussion among data junkies over the technical merits of MapReduce versus traditional databases. The conclusion? Databases "were significantly faster and required less code to implement each task, but took longer to tune and load the data," the researchers write. Database clusters were between 3.1 and 6.5 times faster on a "variety of analytic tasks."...

2009/07/10

Over the past year, columnar analytical database vendor ParAccel has methodically proven its claims about speed, scalability and easy deployment. Now it's looking to grow fast.

2009/07/07

MPP, Column-Oriented Analytic Database for Data Warehousing and Analytics

2009/07/03

Relational database management systems (DBMSs) have been remarkably successful in capturing the DBMS marketplace. They are selling 'one size fits all'; i.e., a single relational engine appropriate for all DBMS needs. Moreover, the code line from all of the major vendors is quite elderly, in all cases dating from the 1980s. Hence, the major vendors sell software that is a quarter century old, and has been extended and morphed to meet today’s needs. In my opinion, these legacy systems are at the end of their useful life. They deserve to be sent to the 'home for tired software.' Here's why....

2009/06/26

LucidDB is the first and only open-source RDBMS purpose-built entirely for data warehousing and business intelligence. It is based on architectural cornerstones such as column-store, bitmap indexing, hash join/aggregation, and page-level multiversioning. Most database systems (both proprietary and open-source) start life with a focus on transaction processing capabilities, then get analytical capabilities bolted on as an afterthought (if at all). By contrast, every component of LucidDB was designed with the requirements of flexible, high-performance data integration and sophisticated query processing in mind. Moreover, comprehensiveness within the focused scope of its architecture means simplicity for the user: no DBA required....

2009/06/23

Designed for analytics, ICE is easy to use, simple to manage and ideal for data volumes up to 30 TB and more. ICE combines a column-oriented database with a unique Knowledge Grid architecture to eliminate the complexity of data warehousing.