We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 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 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).

More Read

Location Intelligence and Mobile BI: Advancing Customer Relations in the Finance and Banking Sector
Planview Improves Long-Range Planning Potential
Social Media Analytics – Understanding Your Social Customer and Context
Is Big Data The New Term for Business Intelligence?
Cloud-Based BI for On-Premise Data

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

Best Age Estimation Software in 2026: Which Facial Age Providers Actually Hold Up -- AI-generated illustration
Best Age Estimation Software in 2026: Which Facial Age Providers Actually Hold Up
Artificial Intelligence Exclusive Machine Learning
Top 8 Multi-Cloud Architecture Tools for Automated Infrastructure Design in 2026 -- AI-generated illustration
Top 8 Multi-Cloud Architecture Tools for Automated Infrastructure Design in 2026
Cloud Computing Exclusive IT
6 Top Agentic SDLC Platforms for Enterprise Engineering Organizations -- AI-generated illustration
6 Top Agentic SDLC Platforms for Enterprise Engineering Organizations
Artificial Intelligence Exclusive
6 Best Runtime Intelligence Tools for Debugging AI-Generated Code in 2026 -- AI-generated illustration
6 Best Runtime Intelligence Tools for Debugging AI-Generated Code in 2026
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

image fx (60)
Big DataBusiness IntelligenceExclusive

How Finance & BI Teams Choose Accounting Software

10 Min Read

COSS BI: Open Source, Open Core or Openly Naked?

4 Min Read
business intelligence during COVID
Business Intelligence

Global SMEs Adopt New Business Intelligence Initiatives During COVID-19 Crisis

8 Min Read

Top 9 ways to maintain a healthy BI environment

7 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
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?