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Vertica Advances Analytics through Sophistication and Simplification


The growing volumes of data from the Internet and enterprise places pressure to gain better insights on a more frequent basis continues to be a demanding issue for business and IT. The need to process this data for analytic purposes has over the last couple of decades gotten more complicated than simpler as most of the database technologies have continued to upgrade and layer more overhead to deal with this issues. But the advancements of columnar database technology for accessing and storing data into multiple columns for minimizing server and storage processing time along with the use of MPP (massively parallel processing) to help process the requests for data significantly faster are key technologies that can be brought together for more efficient data processing. My colleague recently called this the analytics and data warehouse renaissance that is challenging the traditional database market and introducing new methods for critical information and analytical requirements of business and IT today.

Vertica is an analytic database technology provider that brings together columnar and MPP capabilities together to meet a class of traditional data-warehousing needs to specific analytic needs that might need to respond in real time or for just more cost effective processing and storage of data. Important enough is the ability to keep a low TCO which I believe is still critical to calculate and that through the support of commodity hardware or operating in the Amazon EC2 Cloud Computing environment or as part of the Amazon Machine Image. Many organizations still spend significantly too much of their budget on servers and storage of their data warehouse that is forced upon them by their technology providers. It is not to say that appliances do not provide a value of simplification but so does the ability to easily place a pre-configured software image on commodity hardware. 

Vertica recently announced version 3.5 which includes what they call FlexStore that provides a combination of design, storage and query execution that helps in the workload optimization. Vertica is using intelligent disk utilization capabilities to rank and store columns on disk based on their performance. In addition the support of MapReduce built on the Hadoop open source project as part of the Apache Software foundation that helps with computational process of data stores across distributed systems. This helps make Vertica an accessible analytic store as part of any MapReduce deployments in an enterprise or across the cloud computing environments like Amazon. This new release of Vertica has many other key enhancements from data types to support for Perl and Python to performance improvements in the optimizer and loading of data.

Vertica now has a significant amount of customer ranging from larger enterprises to brand name organizations who are experience this new generation of analytic database technology. Most important is that Vertica is also embracing the community of analytic and BI tools like that from Jaspersoft, MicroStrategy and Pentaho along with integration technology from Informatica that need to interface to their database and work closely for a range of application needs.

The need to broaden our technology awareness of new options for analytics are part of the broadening of the information management agendas of the CIO but also the responsibility of business to understand the choices that can deliver the results based on performance and cost. This is no easy step as these new technologies and databases like Vertica might seem complex but the more you understand the basic context of accessing data that is analytically processed and is loaded from multiple sources, the more you will realize it is more simple than you think. I have seen a lot of advancements since I was involved in analytic databases and data warehouses since the early 90’s and it is about time to see some innovation that moves to dramatically simplify the need for analytic data in business at a price point just about anyone can afford.

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