WHITE PAPER:
This white paper provides and overview of the Intel® Tera-scale Computing Research Program, Intel's overarching effort to shape the future of Intel processors and platforms. Learn about the heart of Intel's research-achieving c...
WHITE PAPER:
Read this paper to learn how combining a high performance batch programming and execution model with a high performance analytical database provides significant business benefits for a number of different types of applications.
WHITE PAPER:
The focus of this IDC white paper is to compare quad-core processors and single-core processors. It then explores the market adoption, customer value proposition and adoption plans for Intel's quad-core technology processor through ...
WHITE PAPER:
Read this white paper for an examination of a new software development language and technology called SequenceL, as well as a description of how it works, why there is a need for it and how well it performs in parallel environments.
WHITE PAPER:
Column-based databases can be slow deleting and updating data. Vertica’s Analytic Database is designed specifically for storing and querying large datasets. Vertica’s differentiator is that it combines a columnar database engine with MPP and shared-nothing architecture, aggressive data-compression rates, and high availability.
WHITE PAPER:
This paper examines the increased business challenges in structured finance, the impact on the underlying enabling technologies, and describes how the use of Vertica’s column store, massively parallel processing (MPP) approach to database management and analytic processing can address some of these challenges.
WHITE PAPER:
It may be surprising to find that Zynga is performing some of the most advanced analytics anywhere. With a user base of over 250 million monthly active users, this white paper describes why Zynga uses the Vertica Analytics Platform to improve its business and game features.
WHITE PAPER:
In order to ensure the enterprise data warehouse will get the optimal performance and will scale as your data set grows you need to get three fundamental things correct, the hardware configuration, the data model and the data loading process.