EducationSoftwareStrategy.com
StrategyCommunity

Knowledge Base

Product

Community

Knowledge Base

TopicsBrowse ArticlesDeveloper Zone

Product

Download SoftwareProduct DocumentationSecurity Hub

Education

Tutorial VideosSolution GalleryEducation courses

Community

GuidelinesGrandmastersEvents
x_social-icon_white.svglinkedin_social-icon_white.svg
Strategy logoCommunity

© Strategy Inc. All Rights Reserved.

LegalTerms of UsePrivacy Policy
  1. Home
  2. Topics

KB438759: In-memory Cube Reporting: OLAP vs MTDI and Best Practices


Community Admin

• Strategy


The attached document details the differences between OLAP and MTDI cubes, including the basis for the performance profile of each and the available functionality for these two types of in-memory cubes, as well as best practices to tune performance for the publication and reporting off these cubes.

OVERVIEW:
The document attached to this Knowledge Base article reviews the following topics, OLAP vs MTDI Cubes and the differences, Data Processing and Storage In-Memory, Cube Reporting and Performance Considerations, Useful logs for troubleshooting. 
INTRODUCTION:
Strategy’s in-memory cube technology has been generally referred to as PRIME cubes. PRIME stands for Parallel Relational In-Memory Engine, and it engulfs two types of in-memory cubes: OLAP cubes, or the traditional Intelligent Cubes, and Multi-table Data Import (MTDI) cubes. Both types of cubes leverage the new partitioning functionality that allows loading more data to memory and querying this data in a parallel fashion leveraging multi-core hardware architectures. 
The most obvious difference between OLAP and MTDI cubes is how they are authored and created; OLAP cubes are only authored through Developer and are tightly coupled to a Strategy project schema. Because of this, OLAP cubes are traditionally built and maintained by advanced BI developers or architects. On the other hand, MTDI cubes are authored through Strategy Web, and through Visual Insight or Strategy Workstation, these cubes do not need a project schema, and therefore business users can themselves create these cubes by directly loading data from one or more sources and determine what columns are attributes, along with their relationships, and which are metrics. MTDI cubes are the self-service in-memory solution.
The attached document details the differences between these two types of cubes, and these distinctions are the basis for the performance profile and available functionality for these two types of in-memory cubes, along with best practices for both publishing, modeling and querying these cubes.
Disclaimers and Limitation of Liabilities
Disclaimer:The attached document is provided "as is" and without warranty of any kind. Strategy Expressly disclaims all warranties, express, implied or statutory, including, without limitation, the implied warranties of merchantability, fitness for a particular purpose, satisfactory quality and noninfringement.
Limitation of Liability: Strategy shall have no liability to licensee for any damages of any kind, including, but not limited to, liability for direct, indirect, special, incidental or consequential, damages (which shall include, but not be limited to, loss of data or information, loss of revenue or anticipated profits or lost business). KB438759


Comment

0 comments

Details

Knowledge Article

Published:

October 11, 2017

Last Updated:

February 26, 2024