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?
“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:
- RAM is cheaper, but it’s not cheap. Disk was and always will be cheaper than RAM.
- 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.
- 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:
- RAM is cheaper, but it’s not cheap. Disk was and always will be cheaper than RAM.
- 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.
- 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.
