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Our Process We Threw Out Preconceptions and We Threw Out Preconceptions and Left No Stone Unturned Left No Stone Unturned We looked at white papers, articles, Gartner and Forrester We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral collecting a mountain of reports, and marketing collateral collecting a mountain of supporting documents supporting documents We got NDAs, looked at user manuals, admin manuals, We got NDAs, looked at user manuals, admin manuals, internal case studies, talked to vendor engineers, some internal case studies, talked to vendor engineers, some without salespeople knowing without salespeople knowing We went to User Conferences We went to User Conferences We saw customer and partner presentations, and reviewed We saw customer and partner presentations, and reviewed slides from many more slides from many more We Talked to vendor partners and independent consultants We Talked to vendor partners and independent consultants We peered inside of racks trying to figure out how these We peered inside of racks trying to figure out how these thing were built thing were built We went to Tuning and Training classes to see just how We went to Tuning and Training classes to see just how easy things really were easy things really were We Talked to customers in our vertical: CBS Interactive We Talked to customers in our vertical: CBS Interactive (formerly CNet), 24/7 RealMedia, Paypal, Travelocity, (formerly CNet), 24/7 RealMedia, Paypal, Travelocity, Ebay, Netflix Ebay, Netflix

Our Process We Threw Out Preconceptions and Left No Stone Unturned We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral

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Page 1: Our Process We Threw Out Preconceptions and Left No Stone Unturned We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral

Our Process

We Threw Out Preconceptions and We Threw Out Preconceptions and Left No Stone UnturnedLeft No Stone Unturned

• We looked at white papers, articles, Gartner and Forrester reports, and We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral collecting a mountain of supporting documentsmarketing collateral collecting a mountain of supporting documents

• We got NDAs, looked at user manuals, admin manuals, internal case We got NDAs, looked at user manuals, admin manuals, internal case studies, talked to vendor engineers, some without salespeople studies, talked to vendor engineers, some without salespeople knowingknowing

• We went to User Conferences We went to User Conferences • We saw customer and partner presentations, and reviewed slides from We saw customer and partner presentations, and reviewed slides from

many moremany more• We Talked to vendor partners and independent consultantsWe Talked to vendor partners and independent consultants• We peered inside of racks trying to figure out how these thing were We peered inside of racks trying to figure out how these thing were

builtbuilt• We went to Tuning and Training classes to see just how easy things We went to Tuning and Training classes to see just how easy things

really werereally were• We Talked to customers in our vertical: CBS Interactive (formerly We Talked to customers in our vertical: CBS Interactive (formerly

CNet), 24/7 RealMedia, Paypal, Travelocity, Ebay, NetflixCNet), 24/7 RealMedia, Paypal, Travelocity, Ebay, Netflix

Page 2: Our Process We Threw Out Preconceptions and Left No Stone Unturned We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral

Our Findings On Our 3 Vendor FinalistsOracleOracle• Highly horizontally scaled RAC best approach for doing large Data Warehousing on Oracle• Oracle HP Database Machine potentially represents best approach of the above, but is very new and unproven• Parallelism limitations, quasi-MPP, “share everything” clustering complexities, delivery and management

complexities still exist as they do for us today, and will increase to make things work optimally

Teradata• The 2550 Appliance has a 140TB limit with a vendor promise to extend past 200TB by 2010, with an 8 rack 32

node 100TB footprint, is built on very proven Teradata software, in an appliance that has yet to be implemented in a customer production environment. Fundamentally it has the potential to deliver great performance at an affordable price.

• Is true Data Warehouse best practice MPP share nothing architecture• Development and administration complexity is significant but manageable with acquisition of one expert resource• Teradata has more of a Fortune 500 alignment with a focus on extremely mixed workload and extremely large

concurrent users loads Netezza• Advanced always-on-do-nothing column-wise compression achieving 2-4X compression on a 10800 appliance

has pushed Netezza’s user data capacity past 200TB with NYSE achieving 2.3X compression holding 168TB of user data occupying only 73TB of physical user space out of the available 100TB on a 10800.

• Is true Data Warehouse best practice MPP share nothing architecture• There is a high E-business focus with customers CNet and 24/7 RealMedia doing things strikingly similar to what

we need to do. Nielsen, MasterCard, Nationwide, Amazon, Yum! among their 200 customers.• Customer conversation and attendance of tuning classes attests administration and development with Netezza is

drop dead “stupid” simple.• Outrageously satisfied customers and a story of great strides of maturity over last 2 years• Well aligned with MicroStrategy and Informatica. Vendor partners like Edge building packaged clickstream

solutions on Netezza. Acquisition and integration of spatial capabilities.• Zonemaps, sorted projected materialized views, guaranteed resource allocation, prioritized query execution, short

query bias, and incremental backups successfully address most of the complaints of Netezza in the past

Page 3: Our Process We Threw Out Preconceptions and Left No Stone Unturned We looked at white papers, articles, Gartner and Forrester reports, and marketing collateral

Recommendations

Absolute best practice is to prove out solution in a POC

• Netezza is Primary Platform Choice Pre-POC– Key deciding factors

• Speed of delivery• Low Support needs• Performance (expected)• Real world success on exact platform• Small footprint, low power• Success in our vertical

– Key things that MUST be proven in POC and further investigation• A 2x compression needs to be achieved; a 1.5X is an absolute minimum.• Performance across all scenarios• Ability to backup and survive hardware failures

If Primary Platform Choice Fails to Deliver

• Teradata on 2550 is Secondary Option ATeradata is secondary choice if performance and ability to deliver are key factors. Teradata may not be a viable option if 8 racks for 2009 and 16 racks for 2010 hits data center limitations.

• Oracle HP Database Machine or Similar Oracle RAC is Secondary Option BOracle is secondary choice if small footprint and use of existing resources (human and system) are key factors. Tuning, time to develop, care and feeding would be no better than today. Risk that performance and scaling would still be a challenge. Recommend start with Database Machine and scale back into stability.