HP Vertica General manager Sets Sights on Next Generation of Anywhere Analytics Platform

HP Vertica General manager Sets Sights on Next Generation
of Anywhere Analytics Platform
Transcript of a BriefingsDirect podcast on how HP Vertica is evolving to meet the needs of
enterprises as data continues to grow.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Dana Gardner: Hello, and welcome to the next edition of the HP Discover Performance
Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for
this ongoing discussion of IT innovation and how it’s making an impact on
people’s lives.
Once again, we’re focusing on how IT leaders are improving their business
performance for better access, use and analysis of their data and information.
This time we’re coming to you directly from the HP Vertica Big Data
Conference in Boston and we're delighted to welcome the General Manager of
HP Vertica to his debut on BriefingsDirect. [Disclosure: HP is a sponsor of BriefingsDirect
podcasts.]
Please join me in welcoming Colin Mahony, the General Manager at HP Vertica. Good to have
you with us, Colin.
Colin Mahony: Thanks, Dana. It’s great to be here. I appreciate you having me.
Gardner: Well, it's been well over two years since HP acquired Vertica and, as we begin the of
the 2013 Big Data Conference, how would you best characterize how Vertica has evolved since
its founding back in 2005?
Mahony: Oh, wow. We’ve evolved quite a bit. It’s been a busy couple of years here, certainly
post the acquisition, but I think at a high level, we’ve really shifted and expanded from being an
MPP column store, very narrowly-focused database company, really into an analytic platform
company.
With that comes several developments, obviously on the product side, but also as an
organization, going through that maturation in terms of being able to operate at a global scale
across the spectrum of what you would expect an analytics provider to offer.
Gardner: And how do you characterize the difference between a store and a platform? Are there
many ecosystem players or is this an organic evolution of your capabilities or both?
Mahony: It’s both the ecosystem and the tools that you interact with, and of course, we support a
very rich and vibrant ecosystem of business-intelligencve (BI) tools, extract, transform and load

(ETL) tools, and other types of management tools. Not just the ecosystem around it, but also
looking within our own products.
So it's adding a lot of the capabilities like backup and recovery, additional analytics capabilities
beyond just standard SQL with the SDKs that Vertica supports, the ability to run
both the procedural and the other types of code within the product, being able to
express things like MapReduce beyond what a traditional database system would
do.
Since the founding of the company, we've tried to take the best part of the database
world and the best parts of the SQL world, but address the most challenging issues
that traditional databases have had. So whether it is scalability or it’s being able to
run things beyond SQL or it’s just the performance, those are all the things that we have taken
into account while we built Vertica, and I think we have always been on the fast track to a
platform.
We knew it would be a journey and we knew that building a product and a platform from the
bottom up is not an easy thing, but we also knew that once we got there, once we sort of crossed
that chasm, if you will, then all those decisions that made in the beginning about this product and
building an engine from the bottom up would pay off.
Platform modularity
For probably the last year, that's where we’ve been. Right now, we're seeing that it’s easy to
add functionality to the platform because of the modularity of the platform, and we
can add that functionality without giving up any of the performance.
For me, it’s probably the most exciting time. Being part of HP offers us so
many things that make it a lot easier to become a platform, not only on the
development side, but a much greater ecosystem, a global scale, being able to
support customers globally 24/7.
Gardner: This is a large conference. I'm pretty impressed with the attendance, but for our
audience, this might be an introduction. Why don’t you tell our listeners and readers a bit more
about yourself and your background?
Mahony: I've been with Vertica since the beginning. In fact, long before Vertica, my background
has always databases. I've always loved computer science, and had a minor in computer science
in my undergraduate degree. In my ﬁrst job out of school, I was taking databases -- it's one of our
competitors now, so I won't name them -- but I was using their database, working with civilian
US Government clients, and getting a lot of information published up to the web in the earliest
days of the web.

I had a couple of other roles, but they were always very technology focused. Then I got my
MBA on the business side and went into venture capital for seven years. That's where I met Mike
Stonebraker, the founder of Vertica.
I just loved the idea, everything I knew about databases and the challenges of traditional database
and everything I knew about the new world order of information -- at the time we didn’t even
talk about the term big data -- just seem to align really well.
So I decided to leave the dark side of venture capital and I jumped into something that I have
been incredibly passionate about. If you look at that lifecycle even my own background with
Vertica and where we’ve come, it’s just been a great. The timing was great and as always it takes
a lot more than just great technology and great people.
There is deﬁnitely a lot of luck and timing, and I had the fortune of stepping into the right market
at the right time, being part of a great team, and learning from a lot of great people along the
way.
This is our ﬁrst user conference. It’s ironic that we've never had one before, but I think also this
is a testament to that scale I was referring to with what HP can bring. We have wanted a user
conference since the beginning. Obviously, it takes some critical mass to get there which we now
have, but also it takes the support of an organization that knows how to do these conferences and
understand the value of them.
So it's just wonderful to be here. It’s wonderful to see all of these partners, customers, employees
and friends of Vertica and HP here in Boston, of course Vertica’s hometown, so truly exciting.
Gardner: You mentioned the marketplace and the timing. I have to go back to that because in
2005, while scale and performance were very important. This whole notion of big data being so
prevalent in the market really hadn't happened yet. What’s the state of the union, if you will, with
this marketplace? Do more and more IT functions and business functions begin and end with Big
data? It seems to be at the center of so many things.
Exponential growth
Mahony: It is. To go back to the founding of Vertica, I remember when Mike Stonebraker was
giving the early presentations on the need for it. He talked a lot about the exponential growth of
data and how that was outpacing any laws like Moore’s law or other hardware laws. So much
information was being created, there was no way that just using more paralyzed hardware was
going to be able to address the issue.
The state of the union back then was, just as you said, there was no such thing as big data, but I
think Mike, as a visionary, knew what was going to happen in the industry, and it has happened.

It wasn’t a long time ago, but I remember that I was trying to find our first sample dataset that
was over a terabyte and we had a difficult time finding it. When we would talk to the early
customers, they looked at us like we were crazy when we were asking about a terabyte.
We have an easy time now finding terabytes of data. The state of the union today is that what's
driving so much around big data is that you have obviously the volume, variety, and velocity that
we talk about often, but what's really driving those three things is human information, whether
it's social media, tweets, or expressive content that’s just so prevalent right now, as well machine
information.
If you look at the traditional structured database market by any number, it’s a small percentage of
the amount of data that’s out there. The strength of Vertica, and really the strength of HP overall,
is that we have the best assets for the unstructured human information in Autonomy, as well as
the best assets when it comes to machine information and large data.
That has some structure. It’s semi-structured information, but it’s not your traditional transaction
system. The power of all of that data comes together when you can have an engine that applies
some structure to it and then is able to deliver the analytics that the organization needs. It's both
IT as well as line of business, and even this new category we often talk about, which is the data
scientist.
One of the great things about this show here is that we’ve got Billy Beane of Moneyball fame as
our keynote speaker. The reason that we wanted Billy to come speak here is that Moneyball is
exactly what’s happening right now in the world when it comes to big data.
You have the data scientist or the statistician, you have the line of business folks, and you have
IT. They all have a part to play in the success of how information is used in companies. By
bringing them together and by making the software that much easier for them to come together
and solve these problems, you can create very real and differentiated value within organization.
So Moneyball is exactly what’s happening, certainly in corporate America, but also in
government and in many other institutions that want to leverage information to be more efficient
and create a competitive advantage.
Gardner: Before we delve into the latest and greatest with Vertica, let’s put some context around
this. It’s only been a few months since the HP Discover 2013 Conference in Las Vegas where the
HAVEn Initiative was announced. This puts Vertica in a very prominent place among other HP
properties, technologies, platforms and approaches to solving this big data issue. Recap for us, if
you would, what HAVEn is and why Vertica formed such an important pillar for this larger HP
initiative?

Big-data lake
Mahony: What companies are looking for is this notion of the big-data lake. To me, it can
mean many different things, but at the end of the day, companies want to take all the information
assets that they have and they want to put them into a safe place, but a place where access to that
information can be used by many different constituencies, whether it's IT, line of business, or
data scientist.
So the notion of having a safe place, a harbor, or a port is what we announced as HP HAVEn,
which is HP’s big data platform. It is primarily for analytics, but it can be used for just about
anything when it comes to information and data.
What's so important about information right now is that there are different constituencies in the
companies that want to take the information. First of all they want to capture all the information,
not just structured, not just unstructured, but 100 percent of their information.
They want to get it to a place where they can leverage it and use it for a lot of different use cases,
but the ﬁrst part is get that information into the right place. For us, that is one of three
components of HAVEn, which is the connectors.
We have over 700 connectors as part of HAVEn coming from Autonomy, coming from our
Enterprise Security Group, the ArcSight core Logger and those connectors. That can be human
information, extreme log information, or traditional database structured information.
Step one is the connectors to get these components. Step two is to put that data into the best
engine for that data. Vertica obviously is one component, but you also have the Autonomy IDOL
Engine, you have the ArcSight Logger engine, and also open-source technologies like Hadoop,
which is actually the HP HAVEn. So we’ve got a place to put the information.
Step three is any N number of applications. What I'm seeing happening in the industry right now
is just like we went from mainframe to client-server, and client-server to LAN, we're in a period
now where applications are being developed. They're certainly web-based and distributed, but
they're also analytical in nature.
They're driven by vast volumes of information and they close the loop, meaning that the
experiences that are happening with an application, if you're driving a car, or whatever it might
be, information is being passed, closed loop, back to a system that can then optimize the
experience. That is creating a new class of applications.
For that new class of applications, you need the platform to be able to drive those. What we're
bringing together in HAVEn is Hadoop, Autonomy, Vertica, Enterprise Security, core assets, and
the N number of applications.

At Discover, we announced some of our own internal applications, which are powered by the
HAVEn platforms. We announced our HP Analytics offering, which is built using Hadoop,
Vertica, Enterprise Security, and Autonomy assets.
About community
We're making some of our own applications, but this is about the community and getting
people to be able to build new set of applications that can use these components to really change
how people are interacting with their data.
That’s HAVEn, and I am always careful to point out to people that HAVEn itself is not a product,
but it's a platform and it’s a broader platform than the one that is just Vertica, Autonomy, or
Enterprise Security. It’s a platform where 1+1+1+1+1, instead of equaling 5, should equal 8 or
10 or 12, and that's the goal. Of course, it's also a roadmap into areas that each of these
components are working on to bring those closer together. So it’s exciting.
Gardner: Let’s look a bit more specifically at Vertica and try to factor why it’s differentiated in
the market, but then also get a sense of where it’s going.
One of the things that strikes me about the market nowadays is that there seems to be a sense of
tradeoffs going on when organizations are trying to pick their data engine or their platform. They
have a set of value on one side, but it’s opposed by value on the other. They can’t have
everything. One size does not fit all.
So how are you at Vertica able to help people deal with these tradeoffs that they're facing when it
comes to a next-generation data platform?
Mahony: Before I explain the tradeoffs, I couldn’t agree with you more, Dana. In fact, Vertica
was founded on the premise that one size does not fit all. Using a single OLTP transactional
database to do everything, including analytics, just doesn't make a lot of sense.
If you think about the areas that the people have to trade off, usually it’s scale for performance or
analytics functionality for performance. One of things that I've spent a lot of time looking at is,
especially over the last couple of years, is just some of the alternative platforms, not just for
analytics, but for all of the different data needs.
You can take something like Hadoop as an example. Hadoop really is a distributed file system
and has capabilities to run rudimentary analytics and transform processed data. But I think what
people love about Hadoop is that it's really easy to load data into Hadoop. You don't have to
define the schema or anything.
Instead of schema on write or load time, it’s schema on read time. People like that. They also like
at least the perception that it is free and the scalability of it. On the database side, what people
love about the database is that you're going to get really good performance, because the data is

structured. If you're using a NexGen MPP platform like Vertica, you'll get the performance of the
scalability.
So what we’re trying to do and what we've always done a pretty good job of at Vertica is look at
the things that would make sense for Vertica to do. We look at expanding the platform in ways
that, number one, we have the expertise and the capability to do, not only from the development
standpoint, but from the support standpoint. And number two, we have the ability to create
something differentiated. If we don't, or it’s not core, then we won’t do it, sticking to the purity
of one size doesn’t ﬁt all.
Hadoop-like
We've been doing a lot of work in areas like making it easier to get the data into the platform,
doing more with it, making it seem much more like a Hadoop-like environment. You can look at
our past releases and see that there's been a lot of work done on that and we continue to make
those investments.
One thing has been consistent at Vertica since the beginning. What we focus on is to make it
really easy for people to get information onto the platform. Then, we make sure we continue to
deliver new capabilities, performance, and functionality within the platform.
We make sure we’re enabling our customers and partners to deploy Vertica anywhere and
everywhere, whether it’s cloud appliances, software, or the like. Those are the three tenets of the
company. It’s all around this notion of making data matter and help people make better decisions
that lead to better outcomes with superior information.
There's so much that can be done in this space, but I think the key for us is to focus on the things
that we know we do really well. The good news is that it's such a large space with so many
demands that we know we can make a huge impact without trying to take on the world. We know
we can make a huge impact in what we’re doing.
I think you'll continue to see some interesting developments along the lines of what I'm
describing, and it's very much in line with where we've been.
Gardner: While we're at the User Conference, there are some great use cases and some
examples. It's one of my favorite points of communication that it's always better to show than to
tell.
Of the various user organizations and use cases here, are there are any that jump at you
personally when you think about what Vertica started out as and what it became? Are there any
ways that some users are putting this to work to really capture, "This is what we intended, and
this is what we went through those paces to allow, to encourage, and to now see the fruits of? "
So from all of the happenings here with the conference, what sort of gets your blood ﬂowing?

Mahony: One thing I've certainly noticed over the years with our customers is that the shiny
object of why a customer chooses Vertica may look very different across our customers. For
some, it's the price. For some, it's the performance and the scale, massive volumes. For some it's
a particular analytic function or several pattern matching capabilities. And for others, it's
something entirely different.
But what's so exciting; especially about this conference, is that no matter what on-ramp they
take, they tend to find a lot of the other capabilities once they get on. Hopefully, here at the
conference, we're going to accelerate some of that just by getting our customers and our partners
together in an environment where they can share stories.
Partners and customers
In fact, if you look at the agenda for the conference, it's very light on Vertica presentations. It's
very heavy on partner and customer presentations, because this is the time that we want our
partners and our customers to learn from each other. We want them to talk about how they are
using it.
To answer your question directly, what gets me most jazzed up is when a customer is taking
advantage of nearly everything that we do. Again, it's a cycle. It's not something that can happen
immediately.
There are so many customers here that have been with us for four or five years and had just been
great partners for the Vertica organization in terms of the feature we are developing and the
direction that we are taking the product. They tend to be the ones who are using just about every
feature in the product. So it gets me really excited.
I have got a customer that's got massive volumes of information, lot of diversity in the
information, many different lines of business constituents who are accessing the information,
data scientists, DBAs, programmers, different people who are creating applications and keeping
the system up and through all that change in the organization.
Sometimes it's not only change in the organization, but potentially change in the industry and
changing the way that people are interacting with data and may be changing healthcare
outcomes, or drastically improving the quality of mobile phone service or other types of services.
So there isn't any one customer of whom I'd say, "You have to go see these guys." The reality is
that you should see all of our customers and hear what they have to say. For me, that's the most
important part of this conference.
It is about the connection between our customers and our partners, so that they can talk to each
other. We can just be a fly on the wall and listen to some of the things that they're saying, good,
bad, or ugly -- hopefully very good. But we can even hear things that they want us to improve.

That's an important part of any company, certainly a software company, and that's what we're
hoping to get out of it. For our customers and partners, they're going to get a lot of out of this just
by talking to each other.
Gardner: Colin, what about the notion of business transformation. We've been hearing about
this for 30 years. It's been big part of the academic work in business schools. Process re-
engineering has evolved into balance scorecards, and the flavor of the day is about how to
change the nature of companies.
But it strikes me that this whole greater than the sum of the parts that you alluded to earlier,
where data and analytics is made more available across easier applications to morph that, is
inside the company that can then access more types of information across the boundaries of the
organization into supply chain and ecosystems.
Getting more detailed information in real time about the customers and the marketplace probably
has as much or more of a opportunity to transform businesses than just about anything else that's
happened, with the possible exception of the Internet itself, over the past 20 years.
More than technology
So without going too much into a hype curve, the interest of the incredible amount of attention
paid to big data in the past few years is about more than the technology. It's really about an
empirical data-driven approach, a cultural shift if you will, within businesses. How you have
been seeing that manifest itself here at the conference?
Mahony: It's an enormous opportunity for business transformation and definitely the whole is
greater than the sum of the parts. What makes companies really successful with information is
not trying to boil the ocean, not trying to do a traditional enterprise data warehouse project that's
going to take 24 months, if you're lucky, 36 most likely.
They’ll end up with some monolithic inflexible platform that will probably be outdated by the
time it gets deployed. What is making a lot of companies successful is they find a particular use,
they find a problem area that they want to drill down on, and they mobilize to do it.
For that, they need a solution that is quickly deployed, but also has that capability to become
something much larger. Whether it's Vertica, Talend, or any of the other portfolios that we offer,
we strive to make sure that somebody can get up and running quickly, whether it's Autonomy and
human information analytics, Vertica and machine data or other types of transactional structured
data.
The most important thing is that you find that business case, you focus on it, and prove very
quickly. There's something we refer to as “Time to Terabyte,” which is less than a month,
typically for Vertica. You get a return on investment (ROI) in less than a month for the

investments that you made. If you prove that out, then everybody in the organization is happy,
the line of business, the technology folks in IT, even the statisticians, data scientists.
From there, you start expanding the project, and that's exactly how we win most of our
customers. We very rarely go in and say, "Buy an enterprise license for our product across the
company." We certainly do those, but more typically we get into a business unit, we find the
acute pain, and we solve that problem.
What they're betting on is the ability for us to expand and for them to expand in this platform.
That's why we are, on the one hand, all about the platform and the integration, but on the other
hand, not about to lose the flexibility and the modularity of what we do, because that's also a
huge differentiator for HP's portfolio.
I think that this is a wonderful time in the world of business transformation, and I think, unlike
what has been talked about for the last 30 years, you now have the data that can back it up and
prove it in real-time to the organization.
That's the big difference. You gave the balanced scorecard as an example. If you look at the
balance scorecard methodology, you can take that methodology and drill down into a thousand
fields of detail and be able to get that information in real time. That's the opportunity here, and
that's I think why this market is so huge.
It's not just about faster speeds and feeds. It's about fundamentally stepping back and asking how
we're running this business. What assets, especially information assets, do we have that could
dramatically boost the productivity to the same extent that computers, when they were first
introduced, boosted productivity. That's the goal that everybody is looking for when it comes to
information.
Cloud and hybrid
Gardner: For our last item today, I wonder if we could take out our crystal ball apparatus and
try to do a little blue-sky thinking. One of the other big trends these days of course is cloud
computing and hybrid models for the distribution of workloads for applications, but also for data.
I'm wondering, as we go down this journey over the next year or two, how do big data and cloud
computing come together?
There's this notion of an analytics platform-as-a-service (PaaS) deploy for developers, but now
maybe more for data scientists and for those that are doing BI and other analytic chores. How do
you foresee some of this whole greater than the sum of the parts extending beyond the technical
capabilities into the deployment models and what is that portend, for additional paybacks or
payoffs?
Mahony: As I mentioned in terms of the three things that we are focused on, number one is
make it easy to get data into the platform. Number two is do a lot more with the platform, so that

there is better analytic capabilities, better pattern matching, and better analytics packs on top of
it.
Number three is make sure you can deploy Vertica everywhere, and in the everywhere and
anywhere categories, the cloud is certainly the first name that comes to mind. That is absolutely
the future of computing. In some ways, I guess, it's the past, but it's interesting how the past
repeats itself.
We do run Vertica on hosted environments like Amazon cloud. We're in a private beta on the HP
Cloud Service. So there are definitely offerings and developments that that has been underway
here at Vertica for a while.
We embrace that, and to us, it's not mutually exclusive. What you described in the hybrid
environment where you can run certain things locally. You can burst up to the cloud to do other
workloads, especially if you're looking to pull some quick processing power and storage. That's
going to be the future and that's the way, just like any other utilities, that we're going to consume
some of these capabilities.
This is one of the strengths of a company the size and scale of HP. We have these offerings,
whether it's software only, appliance, or cloud. We have the ability to deliver however the
customer wants it, and we can also provide not only the flexible technologies, but the flexible
business capabilities to make that happen with a lot of ease.
It's an exciting time. If you look at the pillars of the HP, we have cloud, mobility, big data, and
security. All four of those pillars tie well into one another, because they're all related. Of course,
all these activities that are happening up on the cloud are generating a lot of information,
information that will be analyzed I am sure in many different ways.
So it's something that kind of feeds on itself, the same way the mobility does. All of that is a
good thing for the analytic space, wherever it is. The final thing I would say is that the most
important thing about analytics is that you do want it embedded into the various applications, just
like when you are driving a car, you just want the GPS system to tell you where you are going.
Analytics is the same. You want it within the context of whatever it is that you are doing. Given
that so many things are going to be served off the cloud, it's natural that that's the place that will
host some of the analytics as well.
So it's an incredibly exciting time, and we're looking forward to having many more of these User
Conferences and are certainly going to enjoy the rest of the show this week.
Gardner: Well great. I'm afraid we will have to leave it there. We've been learning more about
the ongoing evolution of the HP Vertica platform and its capabilities, and we've developed better
understanding about Vertica's growing role and making among the most challenging big data
analytic chores more successful and impactful.

So, join me in extending a huge thank you to our special guest Colin Mahony, the General
Manager at HP Vertica. Thanks so much.
Mahony: Thank you, Dana.
Gardner: And also thank you to our audience for joining us for this special HP Discover
Performance podcast, coming to you from the HP Vertica Big Data Conference in Boston.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions; your host for this ongoing series of
HP sponsored discussions. Thanks again for listening and come back next time.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Transcript of a BriefingsDirect podcast on how HP Vertica is evolving to meet the needs of
enterprises as data continues to grow. Copyright Interarbor Solutions, LLC, 2005-2013. All
rights reserved.
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