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Cloud Analytics - The Big Four Offerings

Roadmap for enterprises for Cloud Analytics

Cloud Analytics
The term  ‘Analytics On Cloud'  refers to a comprehensive offering of a combination of products that enable enterprises to move their Business Intelligence, Data Warehousing  & Online Analytical processing (OLAP)  workload to a Cloud platform.

While the implementation of Cloud Analytics would take several forms at a high level, the following could be the parts of a Cloud Analytics platform that would be of interest to an enterprise.

  • A Virtualized Infrastructure to support the basic Cloud Tenants to Build a Private Cloud
  • Availability of a Public Cloud Infrastructure for augmenting certain components in a Hybrid model
  • Platform as a Service inline with the underlying Cloud Infrastructure that can support the analytical needs of:
    • Reporting
    • Analysis
    • Dash Boards
    • ETL (Extraction , Transformation & Loading)

It is good news that the major IT pioneers HP, IBM, Oracle and Microsoft have pledged support for Cloud Analytics. The following is an analysis of the offerings from these major players and what Cloud attributes each of these offerings support. The aim is to support Cloud adoption in the Analytics market. All the information about the vendors are taken from the publicly available material on the web.

IBM Stack for Cloud Analytics:

Private Cloud

Public Cloud

PaaS

HYBRID Support

YES

NO

YES

N/A

 

Private Cloud: IBM's smart analytics  system depends on the underlying  Private Cloud offering which is offered in multiple flavors depending on the server needs of the organization.

  • Smart Analytics System 5600,1050, 2050 (For System X Servers/ Windows /Linux)
  • Smart Analytics System 7700 (For Power System Servers / Unix)
  • Smart Analytics System 9600 (For Z series Servers / Mainframe)

Also the Analytical  Appliance is offered through the  Netezza  Appliance product.

PaaS: IBM Smart Analytics Cloud is built upon two key building blocks, IBM Cognos® 8 Business Intelligence software and the IBM System z platform. IBM Cognos 8 BI is a proven and powerful product that provides a complete range of business intelligence and analytics capabilities including reporting, analysis, scorecards and dashboards.IBM Cognos services can be accessed through various ways, including web 2.0 interfaces, a desktop office product, and smart mobile devices.  InfoSphere data warehouse consists of  other supporting components like, DB2 , Federation Server.

HP Stack for Cloud Analytics:

Private Cloud

Public Cloud

PaaS

HYBRID Support

YES

YES

YES

YES

 

Private Cloud: HP already has a strong  private  cloud offering in the form of,  ‘CloudSystem'. The core HP CloudSystem platform is built on  renowned, field-proven BladeSystem Matrix and Cloud Service Automation products. That core platform is fully extensible via HP's Converged Infrastructure portfolio, including HP 3PAR utility storage, HP Tipping Point Security, and core-to-edge HP Networking.

HP is also expected  to  offer an  Analytic Cloud Compliance based on the Vertica  analytical solutions.

PaaS: Vertica  analytical suite is expected to provided the much needed platform support for the above mentioned Private Cloud  offerings. The Vertica  Analytical platform  provides the following building  blocks of a  BI/Analytical application.

  • Real-Time Query & Loading
  • Database Administration and Design Tools
  • High Availability Architecture
  • BI / ETL & Hadoop / MapReduce integration
  • Advanced Analytics
  • Scale Out MPP Architecture
  • Optimizer and Workload management

Public Cloud: HP Enterprise Cloud Services-Compute runs on the HP Converged Infrastructure architectural model, bringing servers, storage, network, software, and security together into an optimized and efficient resource pool.  Portions of the Analytical work load can be run on  public cloud to optimize the workload management.

Hybrid Delivery: HP announced new management solutions to help clients embrace  hybrid delivery models, spanning on-premise, off-premise, physical and virtual environments, enabling faster time to market and increased agility from application investments.

Oracle Stack for Cloud Analytics:

Private Cloud

Public Cloud

PaaS

HYBRID Support

YES

NO

YES

N/A

 

Private Cloud: At the heart of every Oracle Exadata Database Machine are Oracle Exadata Storage Servers, which combine smart storage software and industry-standard hardware to deliver the industry's highest database storage performance. To overcome the limitations of conventional storage, Oracle Exadata Storage Servers use a massively parallel architecture to dramatically increase data bandwidth between the database server and storage.

PaaS: Oracle Exadata Intelligent Warehouses are complete data warehousing solutions tailored to address industry-specific BI requirements. They include Oracle Data Model, Oracle Business Intelligence, Oracle Exadata, Oracle OLAP and Oracle Data Mining.

Microsoft Stack for Cloud Analytics:

Private Cloud

Public Cloud

PaaS

HYBRID Support

YES

YES

YES

YES

 

Private Cloud: The new appliances  are offered  from HP and Microsoft. Each appliance, optimized for SQL Server 2008 R2, is pre-configured and pre-tuned by the experts at Microsoft and HP. The appliances are complete solutions that are simple to acquire and deploy, high performing, highly secure and energy efficient. By deploying an appliance instead of building a solution, businesses reduce investment, drastically accelerate time to value, and enable IT resources to focus on other priorities.

PaaS: Microsoft SQL Server 2008 R2 Parallel Data Warehouse and its massively parallel processing (MPP) architecture to gain scalable performance, flexibility, and hardware choices with the most comprehensive data warehouse solution available.

Microsoft SQL Server 2008 R2 Parallel Data Warehouse is built on MPP technology that provides enterprise-class performance and scalability to hundreds of terabytes at low cost. SQL Server 2008 R2 Parallel Data Warehouse offers flexibility and choice with appliances planned from HP, Bull and future hardware Partners. Through integration with Microsoft Business Intelligence (BI) and extract, transfer, and load (ETL) tools, SQL Server 2008 R2 Parallel Data Warehouse offers the most complete data warehouse solution.

Some of the  Analytical features supported by this platform are

  • Parallel Loader
  • Parallel Database Copy
  • Parallel Backup and Recovery
  • Multiple Physical Instances of Tables
  • MPP Architecture
  • IO & CPU Affinity

Public Cloud: SQL Azure is a cloud-based relational database service built on SQL Server technologies. It provides a highly available, scalable, multi-tenant database service hosted in the cloud. SQL Azure helps to ease provisioning and deployment of multiple databases. Users do not have to install, setup and patch or manage any software. High availability and fault tolerance is built-in and no physical administration is required. But users can use the existing management tools and knowledge in T-SQL of their existing on-premises SQL Server databases.  Microsoft's public cloud offering is extended with  other  BI tools like SSRS, which extends the Analytical needs of the organization .

Hybrid Delivery: Microsoft SQL Azure Data Sync, currently in CTP (Community Technology Preview) is a cloud-based data synchronization service built on Microsoft Sync Framework technologies. It provides bi-directional data synchronization and data management capabilities allowing data to be easily shared between multiple SQL Azure databases and between on-premises and SQL Azure databases.

Summary:
As detailed out in my earlier articles, Cloud Computing & Business Intelligence , OLAP & Cloud, analytical applications on the large amount of data is a key component that can take advantage of agility of Cloud platform.

Extensive support for Cloud Analytics from major vendors clearly indicate that this will be an important  player in the future enterprise  presence on the Cloud. There are differences in the way the enterprises have supported  this initiative, like some support unstructured content and some continue with traditional RDBMS based approach, however overall we get a  wide range of support from major players.

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