Notes on Data Warehouse Appliance Prices - InformationWeek

InformationWeek is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IoT
IoT
Software // Information Management
Commentary
10/19/2010
10:35 AM
Curt Monash
Curt Monash
Commentary
50%
50%

Notes on Data Warehouse Appliance Prices

I'm not terribly motivated to do a detailed analysis of data warehouse appliance list prices, in part because everybody knows that data warehouse appliances tend to be deeply discounted... That said, here are some insights on data warehouse appliance prices...

I'm not terribly motivated to do a detailed analysis of data warehouse appliance list prices, in part because:

  • Everybody knows that in practice data warehouse appliances tend to be deeply discounted from list price.
  • The only realistic metric to use for pricing data warehouse appliances is price-per-terabyte, and people have gotten pretty sick of that one.
That said, here are some insights on data warehouse appliance prices...
  • Reasons people criticize per-terabyte data warehouse appliance price metrics include:
    • Price-per-terabyte metrics ignore issues of throughput, latency, workload, and so on.
    • Price-per-terabyte metrics ignore quality of storage medium (slow disks, fast disks, Flash, etc.)
    • Price-per-terabyte metrics can be radically affected by changes in disk size.
  • Nonetheless, it is common to discuss data warehouse appliance price/terabyte. When one does, it is common to refer to user data rather than some measure of raw disk capacity.
    • Advantages of this approach include:
      • User data is what matters.
      • User data is what users doing product evaluations or setting budgets can best estimate in advance.
      • User data is a reasonable and popular basis for software-only analytic DBMS pricing.
    • Disadvantages of this approach include:
      • It depends on assumptions about compression (and in some cases indexing and so on), which are highly dependent upon the specifics of the data set.
      • Some vendors and users indeed think in terms of raw disk capacity.
  • Oracle perhaps excepted, data warehouse appliance vendors tend to be laudably conservative in the compression assumptions they build into their per-terabyte price metrics.
  • I wrote last year that Netezza provides the traditional industry benchmark for per-terabyte pricing. When I wrote that, the "Netezza price point" had just become a little under $20,000/TB.
  • That was based on 2.25X compression. Since then, Netezza has upgraded its compression. Netezza now quotes 4X compression. Accordingly, Netezza's list price is now around $11,000/TB. (A little below, actually, per Phil Francisco.)
  • As Doug Henschen reports, the EMC Greenplum Data Computing Appliance starts at $1 million for 18 terabytes of uncompressed user data. EMC/Greenplum also cites a 4x compression figure. That all works out to the vicinity of $14,000/TB.
  • And by the way, if you mirror your data on a SAN, you can stuff twice as much into the EMC Greenplum Data Computing Appliance as otherwise, but then you also have to pay for 36 TB of capacity per half-rack appliance on a SAN.
  • Eric Guyer reminded us that Oracle Exadata has high list prices. He also reminded us that Oracle Exadata is apt to be deeply discounted.
  • A couple of versions ago, I outlined the complexities of Exadata pricing.I'm not terribly motivated to do a detailed analysis of data warehouse appliance list prices, in part because everybody knows that data warehouse appliances tend to be deeply discounted... That said, here are some insights on data warehouse appliance prices...

    We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
    Comment  | 
    Print  | 
    More Insights
News
8 AI Trends in Today's Big Enterprise
Jessica Davis, Senior Editor, Enterprise Apps,  9/11/2019
Slideshows
IT Careers: 10 Places to Look for Great Developers
Cynthia Harvey, Freelance Journalist, InformationWeek,  9/4/2019
Commentary
Cloud 2.0: A New Era for Public Cloud
Crystal Bedell, Technology Writer,  9/1/2019
White Papers
Register for InformationWeek Newsletters
Video
Current Issue
Data Science and AI in the Fast Lane
This IT Trend Report will help you gain insight into how quickly and dramatically data science is influencing how enterprises are managed and where they will derive business success. Read the report today!
Slideshows
Flash Poll