Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Are BI Appliances Simply 30 Year Old Databases?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Are BI Appliances Simply 30 Year Old Databases?
Business Intelligence

Are BI Appliances Simply 30 Year Old Databases?

sisense
sisense
9 Min Read
SHARE

In a thought-provoking blog post published by WIT, a business intelligence consulting company in the

In a thought-provoking blog post published by WIT, a business intelligence consulting company in the U.S., the author writes of latest acquisitions relating to Business Intelligence appliances.

BI Appliances

It got me thinking. I’ve been seeing and hearing the term ‘BI appliance’ a lot recently, and whenever I do – I find myself struggling to understand what it means.

More Read

A New Marketplace of Ideas
Investing in smarter infrastructure will create more than 949,000 new jobs in 2009
CRM Database: Unlocking Customer Secrets for Business Growth
Using Business Intelligence to Catch Wasteful US Spending?
SmartData Collective

One characteristic that seems to be commonly identified with BI appliances is that they are a combination of software and hardware that form specific functions that have to do with analytics (i.e business intelligence). WIT’s article lists a few examples, including HANA (SAP), HP Business Decision Appliance (Microsoft), Netezza (acquired by IBM) and Greenplum (acquired by EMC).

But is proprietary hardware really required for a so-called BI appliance? No, it’s not. And indeed, I have noticed numerous references to Vertica (acquired by HP) and ElastiCube (by SiSense) as BI appliances. Interestingly enough, both are software-only solutions (i.e. software appliances).

It makes sense, as it shouldn’t matter if your ‘appliance’ runs on proprietary hardware or commodity hardware, if it essentially does that same thing.

The BI Appliance Wars

In a recent interview and in response to quips made by Netezza’s CEO regarding HP’s latest acquisition, Vertica CEO Chris Lynch had this to say about Netezza:

“Their tag line is ‘The power to question everything’. So the first question is: why do they need proprietary hardware? The second question is: why are they using a database engine that’s based on technology from 1982?”

He is obviously angry, but I agree with the premise of his argument. If you’re in the analytics business and you require proprietary hardware – there’s something seriously wrong with your database software technology. Commodity hardware is so powerful today with 64-bit computing and multi-core CPUs, that it’s hard to imagine what type of BI solution would require proprietary hardware.  That is, if your technology was engineered in the 21st century.

The established vendors are not oblivious to this, but rewriting their entire codebase is not something they are willing to do. So some are partnering and/or merging with hardware companies as an alternative. But at some point, scraping this codebase will be unavoidable, or customers will flee due to availability of much better and cheaper alternatives.

BI Appliance or BI Tool?

As if to toss a little more confusion into the mix, the WIT author asks:

“Though I wonder – with memory becoming cheaper and cheaper and with 64 bit platform, why do you have to have a special appliance? Why not use an in-memory tool with tons of RAM ?“

The question itself indicates a misunderstanding of why appliances exist in the first place, and there are a several answers to this question.  Here are a few:

  1. RAM is cheaper, but it’s not cheap. Disk was and always will be cheaper than RAM.
  2. The price of a computer jumps significantly beyond 64GB.  A PC with 64GB of RAM costs significantly less than a server machine with 65GB of RAM, even though there is supposedly just a single GB of memory difference.
  3. In-memory databases assume that the main bottleneck is I/O.  However, when dealing with large amounts of data, this is no longer true.  At such volumes, bottlenecks are between RAM and CPU.

For more information about this, please read In-Memory BI is Not the Future, It’s the Past.

Post originally appeared here

Are BI Appliances Simply 30 Year Old Databases?

In a thought-provoking blog post published by WIT, a business intelligence consulting company in the U.S., the author writes of latest acquisitions relating to Business Intelligence appliances.

BI Appliances

It got me thinking. I’ve been seeing and hearing the term ‘BI appliance’ a lot recently, and whenever I do – I find myself struggling to understand what it means.

One characteristic that seems to be commonly identified with BI appliances is that they are a combination of software and hardware that form specific functions that have to do with analytics (i.e business intelligence). WIT’s article lists a few examples, including HANA (SAP), HP Business Decision Appliance (Microsoft), Netezza (acquired by IBM) and Greenplum (acquired by EMC).

But is proprietary hardware really required for a so-called BI appliance? No, it’s not. And indeed, I have noticed numerous references to Vertica (acquired by HP) and ElastiCube (by SiSense) as BI appliances. Interestingly enough, both are software-only solutions (i.e. software appliances).

It makes sense, as it shouldn’t matter if your ‘appliance’ runs on proprietary hardware or commodity hardware, if it essentially does that same thing.

The BI Appliance Wars

In a recent interview and in response to quips made by Netezza’s CEO regarding HP’s latest acquisition, Vertica CEO Chris Lynch had this to say about Netezza:

“Their tag line is ‘The power to question everything’. So the first question is: why do they need proprietary hardware? The second question is: why are they using a database engine that’s based on technology from 1982?”

He is obviously angry, but I agree with the premise of his argument. If you’re in the analytics business and you require proprietary hardware – there’s something seriously wrong with your database software technology. Commodity hardware is so powerful today with 64-bit computing and multi-core CPUs, that it’s hard to imagine what type of BI solution would require proprietary hardware.  That is, if your technology was engineered in the 21st century.

The established vendors are not oblivious to this, but rewriting their entire codebase is not something they are willing to do. So some are partnering and/or merging with hardware companies as an alternative. But at some point, scraping this codebase will be unavoidable, or customers will flee due to availability of much better and cheaper alternatives.

BI Appliance or BI Tool?

As if to toss a little more confusion into the mix, the WIT author asks:

“Though I wonder – with memory becoming cheaper and cheaper and with 64 bit platform, why do you have to have a special appliance? Why not use an in-memory tool with tons of RAM ?“

The question itself indicates a misunderstanding of why appliances exist in the first place, and there are a several answers to this question.  Here are a few:

  1. RAM is cheaper, but it’s not cheap. Disk was and always will be cheaper than RAM.
  2. The price of a computer jumps significantly beyond 64GB.  A PC with 64GB of RAM costs significantly less than a server machine with 65GB of RAM, even though there is supposedly just a single GB of memory difference.
  3. In-memory databases assume that the main bottleneck is I/O.  However, when dealing with large amounts of data, this is no longer true.  At such volumes, bottlenecks are between RAM and CPU.

For more information about this, please read In-Memory BI is Not the Future, It’s the Past.

TAGGED:business intelligencehpmicrosoftsapSiSenseVertica
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Please complete: “There are things known and things unknown and in between …”

4 Min Read

Predictive Analytics World New York City Conference Announces Speaker Line-Up

5 Min Read

Microsoft CIO Tony Scott talks about BI

0 Min Read
Analytics-backed investments ideas
AnalyticsBusiness IntelligenceExclusiveMarket Research

6 Analytics Backed Business Investments For 2019

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?