(upbeat music)
>> Narrator: It's theCUBE,
covering the Virtual Vertica Big Data Conference 2020.
Brought to you by Vertica.
>> Dave Vellante: Hello everyone, and welcome
to theCUBE's exclusive coverage
of the Vertica Virtual Big Data Conference.
You're watching theCUBE,
the leader in digital event tech coverage.
And we're broadcasting remotely
from our studios in Palo Alto and Boston.
And, we're pleased to be covering wall-to-wall
this digital event.
Now, as you know, originally BDC was scheduled this week
at the new Encore Hotel and Casino in Boston.
Their theme was "Win big with big data".
Oh sorry, "Win big with data". That's right, got it.
And, I know the community was really looking forward
to that, you know, meet up.
But look, we're making the best of it,
given these uncertain times.
We wish you and your families good health and safety.
And this is the way that we're going to broadcast
for the next several months.
Now, we want to unpack Colin Mahony's keynote,
but, before we do that,
I want to give a little context on the market.
First, theCUBE has covered every BDC since its inception,
since the BDC's inception that is.
It's a very intimate event,
with a heavy emphasis on user content.
Now, historically, the data engineers and DBAs
in the Vertica community,
they comprised the majority of the content at this event.
And, that's going to be the same for this virtual,
or digital, production.
Now, theCUBE is going to be broadcasting for two days.
What we're doing, is we're going to be concurrent
with the Virtual BDC.
We got practitioners that are coming on the show,
DBAs, data engineers, database gurus,
we got a security experts coming on,
and really a great line up.
And, of course, we'll also be hearing from Vertica Execs,
Colin Mahony himself right of the keynote,
folks from product marketing, partners,
and a number of experts,
including some from Micro Focus, which is the, of course,
owner of Vertica.
But I want to take a moment
to share a little bit about the history of Vertica.
The company, as you know,
was founded by Michael Stonebraker.
And, Verica started, really they started out
as a SQL platform for analytics.
It was the first, or at least one of the first,
to really nail the MPP column store trend.
Not only did Vertica have an early mover advantage in MPP,
but the efficiency and scale of its software,
relative to traditional DBMS, and also other MPP players,
is underscored by the fact that Vertica,
and the Vertica brand, really thrives to this day.
But, I have to tell you, it wasn't without some pain.
And, I'll talk a little bit about that,
and really talk about how we got here today.
So first, you know,
you think about traditional transaction databases,
like Oracle or IMBDB tour,
or even enterprise data warehouse platforms like Teradata.
They were simply not purpose-built for big data.
Vertica was.
Along with a whole bunch of other players,
like Netezza, which was bought by IBM,
Aster Data, which is now Teradata, Actian, ParAccel,
which was the basis for Redshift, Amazon's Redshift,
Greenplum was bought, in the early days, by EMC.
And, these companies were really designed to run
as massively parallel systems
that smoked traditional RDBMS and EDW
for particular analytic applications.
You know, back in the big data days,
I often joked that, like an NFL draft,
there was run on MPP players,
like when you see a run on polling guards.
You know, once one goes, they all start to fall.
And that's what you saw with the MPP columnar stores,
IBM, EMC, and then HP getting into the game.
So, it was like 2011, and Leo Apotheker,
he was the new CEO of HP.
Frankly, he has no clue, in my opinion,
with what to do with Vertica,
and totally missed one the biggest trends
of the last decade, the data trend, the big data trend.
HP picked up Vertica for a song, it wasn't disclosed,
but my guess is that it was around 200 million.
So, rather than build
a bunch of smart tokens around Vertica,
which I always call the diamond in the rough,
Apotheker basically permanently altered HP for years.
He kind of ruined HP, in my view,
with a 12 billion dollar purchase of Autonomy,
which turned out to be one of the biggest disasters
in recent M&A history.
HP was forced to spin merge,
and ended up selling most of its software
to Microsoft, Micro Focus.
(laughs)
Luckily, during its time at HP, CEO Meg Whitman,
largely was distracted with what to do with the mess
that she inherited form Apotheker.
So, Vertica was left alone.
Now, the upshot is Colin Mahony,
who was then the GM of Vertica, and still is.
By the way, he's really the CEO,
and he just doesn't have the title,
I actually think they should give that to him.
But anyway, he's been at the helm the whole time.
And Colin, as you'll see in our interview, is a rockstar,
he's got technical and business jobs,
people love him in the community.
Vertica's culture is really engineering driven
and they're all about data.
Despite the fact that Vertica is a 15-year-old company,
they've really kept pace,
and not been polluted by legacy baggage.
Vertica, early on, embraced Hadoop
and the whole open-source movement.
And that helped give it tailwinds.
It leaned heavily into cloud,
as we're going to talk about further this week.
And they got a good story
around machine intelligence and AI.
So, whereas many traditional database players
are really getting hurt, and some are getting killed,
by cloud database providers,
Vertica's actually doing a pretty good job
of servicing its install base,
and is in a reasonable position
to compete for new workloads.
On its last earnings call,
the Micro Focus CFO, Stephen Murdoch,
he said they're investing 70 to 80 million dollars
in two key growth areas, security and Vertica.
Now, Micro Focus is running its Suse play
on these two parts of its business.
What I mean by that, is they're investing
and allowing them to be semi-autonomous,
spending on R&D and go to market.
And, they have no hardware agenda,
unlike when Vertica was part of HP, or HPE,
I guess HP, before the spin out.
Now, let me come back to the big trend in the market today.
And there's something going on
around analytic databases in the cloud.
You've got companies like Snowflake and AWS with Redshift,
as we've reported numerous times,
and they're doing quite well,
they're gaining share,
especially of new workloads that are merging,
particularly in the cloud native space.
They combine scalable compute, storage,
and machine learning, and, importantly,
they're allowing customers to scale, compute, and storage
independent of each other.
Why is that important?
Because you don't have to buy storage
every time you buy compute, or vice versa, in chunks.
So, if you can scale them independently,
you've got granularity.
Vertica is keeping pace.
In talking to customers, Vertica is leaning heavily
into the cloud, supporting all the major cloud platforms,
as we heard from Colin earlier today, adding Google.
And, why my research shows that Vertica has some work to do
in cloud and cloud native, to simplify the experience,
it's more robust in motor stack,
which supports many different environments,
you know deep SQL, acid properties, and DNA
that allows Vertica to compete
with these cloud-native database suppliers.
Now, Vertica might lose out
in some of those native workloads.
But, I have to say, my experience in talking with customers,
if you're looking for a great MMP column store that scales
and runs in the cloud, or on-prem,
Vertica is in a very strong position.
Vertica claims to be the only MPP columnar store
to allow customers to scale, compute,
and storage independently,
both in the cloud
and in hybrid environments on-prem, et cetera,
cross clouds, as well.
So, while Vertica may be at a disadvantage
in a pure cloud native bake-off,
it's more robust in motor stack,
combined with its multi-cloud strategy,
gives Vertica a compelling set of advantages.
So, we heard a lot of this from Colin Mahony,
who announced Vertica 10.0 in his keynote.
He really emphasized Vertica's multi-cloud affinity,
it's Eon Mode, which really allows that separation,
or scaling of compute, independent of storage,
both in the cloud and on-prem.
Vertica 10, according to Mahony,
is making big bets on in-database machine learning,
he talked about that, AI,
and along with some advanced regression techniques.
He talked about PMML models, Python integration,
which was actually something that they talked about doing
with Uber and some other customers.
Now, Mahony also stressed the trend toward object stores.
And, Vertica now supports, let's see S3, with Eon,
S3 Eon in Google Cloud, in addition to AWS,
and then Pure and HDFS, as well, they all support Eon Mode.
Mahony also stressed, as I mentioned earlier,
a big commitment to on-prem
and the whole cloud optionality thing.
So 10.0, according to Colin Mahony,
is all about really doubling down on these industry waves.
As they say, enabling native PMML models,
running them in Vertica,
and really doing all the work
that's required around ML and AI,
they also announced support for TensorFlow.
So, object store optionality is important,
is what he talked about in Eon Mode,
with the news of support for Google Cloud
and, as well as HTFS.
And finally, a big focus on deployment flexibility.
Migration tools, which are a critical focus really
on improving ease of use,
and you hear this from a lot of customers.
So, these are the critical aspects of Vertica 10.0,
and an announcement that we're going to be unpacking all week,
with some of the experts that I talked about.
So, I'm going to close with this.
My long-time co-host, John Furrier, and I
have talked some time about this new cocktail of innovation.
No longer is Moore's law the, really,
mainspring of innovation.
It's now about taking all these data troves,
bringing machine learning and AI into that data
to extract insights,
and then operationalizing those insights at scale,
leveraging cloud.
And, one of the things I always look for from cloud is,
if you've got a cloud play, you can attract innovation
in the form of startups.
It's part of the success equation, certainly for AWS,
and I think it's one of the challenges
for a lot of the legacy on-prem players.
Vertica, I think, has done a pretty good job in this regard.
And, you know, we're going to look this week
for evidence of that innovation.
One of the interviews
that I'm personally excited about this week,
is a new-ish company, I would consider them a startup,
called Zebrium.
What they're doing, is they're applying AI
to do autonomous log monitoring for IT ops.
And, I'm interviewing Larry Lancaster,
who's their CEO, this week,
and I'm going to press him on why he chose to run on Vertica
and not a cloud database.
This guy is a hardcore tech guru
and I want to hear his opinion.
Okay, so keep it right there, stay with us.
We're all over the Vertica Virtual Big Data Conference,
covering in-depth interviews and following all the news.
So, theCUBE is going to be interviewing these folks,
two days, wall-to-wall coverage,
so keep it right there.
We're going to be right back with our next guest,
right after this short break.
This is Dave Vellante and you're watching theCUBE.
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