>> Announcer: Live from San Francisco.
It's the Cube.
Covering Google Cloud Next '19.
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>> Hello everyone, welcome back to the Cube's
live coverage here in San Francisco.
This is day two of Google Cloud Next 2019.
It's the Cube's exclusive coverage.
We are in the middle of the show floor,
all the action.
The keynotes are still going on, a little bit over.
I'm John Furrier, Dave Vellante, Stu Miniman kickin' off,
breakin' down the keynote analysis,
also breakin' down post day one.
All the action in the evening where all the parties are
and all the action on the hallway conversations.
Dave, Stu kickin' off day two.
Day one was settin' the table, new CEO on stage.
Day two gets into the products, really it's about data,
it's a data, AI, machine learning,
it's all about the data cloud, data.
We're seeing the machine learning, data management,
smart analytics, AI and machine learning, and collaborations
the four themes of today.
Google clearly using data as a key value proposition.
Bigtable, BigQuery, machine learning NGA,
and support for auto ML, and for tables.
Big announcements, your thoughts.
>> Yeah, so John, I think answering some of the things
that we brought up yesterday is when Google puts out
their vision of why they should be your partner of choice,
why customers should choose,
we thought that data and AI and ML
would be led right up front, so they kind of buried the lead
a little bit and the question we had coming this week is
can they reclaim that really felt leadership?
You know a couple years ago you had a data,
really that geeky technical science stuff is what Google
is really good at, so I thought they laid out
some really good things.
I think everybody was impressed to see there was
good diversity of customers,
as well as all the Google people.
There were a lot of the women of Google
that you've written about, John, here.
They're showing their chops here.
So, a lot of pieces to go through and everything
from the G Suite and the Chromebooks and security
and privacy is something I like to talk a little about
when we get into it here.
But quite a lot, as you said,
data and AI are at the center of it.
>> And one of the power women dipped to use the Bigtable.
You're seeing BigQuery all that (mumbles) stuff.
Dave, the big theme in the keynote
also was BI with AI, AI with BI.
We've been covering Hadoop space going back what,
10 years of doing the Cube.
The promise of Hadoop, remember those days.
Hadoop came from Google, Cloudera co-opted it,
they merged with Hortonworks.
Hadoop was kind of a small, little sliver of the ecosystem.
Google's now showing what was once the promise of big data,
they're giving demos, they're democratizing,
they're bringing it in for the masses.
We have stories on siliconagle.com kind of outlining this.
But the reality is there now, rubber's hitting the road.
The promise of big data now with Cloud
really changed the game.
Your thoughts 'cause you've been covering this from day one.
>> Well, I think that there's no question
that this is a data game.
And we said early on, John, on the Cube
that the big data war was gonna be won in the Cloud.
The data was gonna reside in the Cloud.
And having now machine intelligence applied to that data
is what's giving companies competitive advantage
and scale and economics.
I was struck by the stats that Google gave at the beginning
of the keynote today.
Google in the last three years has spent 47 billion dollars
on capital expenditures.
This year to date alone, they've spent 13 billion dollars
in cap ex and data centers, 13 billion.
It would take IBM three and a half years to spend that much
in cap ex, it would take Oracle six years.
So, from an economic standpoint and a scale standpoint,
Google, Microsoft, and Amazon are gonna win that game.
There's no question in my mind.
So, John, you know it is a game of scale and data and AI.
What do you think?
>> Well, I mean first of all, Google,
they got a Kubernetes, Stu, the white paper,
they wrote that, they commercialized Kubernetes in a way
that I thought was really well-executed.
Unlike Hadoop, where they left that on the side of the road,
got picked up by Cloudera, Michaels, and Memorall,
Jeff Hammerbacher, we saw what happened with Hadoop.
Kubernetes, they didn't screw that up.
They basically put it out there in the open source system.
The way they get behind CNCM, really positive there.
On the data front, Google's got so much in the tool shed.
All across Google from day one, their legacy is data.
They're data-driven, large scale.
They build software and systems to manage data at scale
at a whole unprecedented level.
I think that they have-- they're well ahead
of the marketplace on the technology
that are inside Google proper, Google Cloud,
Google proper, Alphabet, whatever you wanna call it,
self-driving cars.
The question for Google is, can they bring it together?
They need to hire a team of people to just go out
and just get it all together.
Pull the jewels together and put it
into a coherent platform.
That's kind of the tea leaves that I see
that we're reading here is that Kurian pointed out
in the keynote, we got tons of technology.
The question is can they pull it together in a package
and make it consumable, addressable, programmable.
Programming APIs, we've seen that movie,
this is happening right now.
The next level of innovation for Google is
can they make data programmable?
This is going to be a 10-year opportunity.
If they get that right, they will win big,
they'll move the ball down the field.
You see Amazon going big on SageMaker.
It's all about data, data analytics at scale,
auto machine learning.
These are the tell signs.
Stu, data programmability, they got all the things,
can they bring it to bare?
>> Yeah, well John, one of the things that I saw got
a lot of people excited is if I have,
you know I'm a G Suite customer, we're G Suite customers,
and I'm using spreadsheets,
now I can use BigQuery with that.
So, the power of analytics and big data, I'll be able
to plug that right in, make it really easy.
And, what's interesting is tryin' to squint through,
what was the Google consumer side of the house
that many of us know and have used for lots of years
versus the enterprise, G Suite and Chromebooks and Mobile.
Well, under Diane Greene it was Google Enterprise,
and now it's all part of Google Cloud.
Just when we talked about Microsoft, it's like, well,
is it Azure or is it O365?
Well, is it G Suite or is it Google?
And, the one that I wanna get your guys comment on
is they talked about privacy.
We know Google as a whole Alphabet is 95% plus ad revenue.
And they were very strong out of here and said,
"We do not own your data.
"We will not sell it to a third party."
Privacy, privacy, privacy.
And it's great to hear them say that,
but we all interact and work with Google,
we know all the cloud providers.
The data is an important thing.
When I do AI and ML type activities, I need to be able
to anonymize it and leverage it and train on it.
So, data privacy issue is still something that,
you know I heard what they said,
but there's gotta be some concerns there.
>> I think there's another angle here
that I'd like to talk about, and that's the database.
Google, Amazon, Microsoft, Oracle,
IBM, MICA, Alibaba, all the big cloud guys.
They want your data.
That's why Amazon is spending so much effort
on the database market.
That's why you see Oracle having such
a dominant position in database.
If you look at Google's announcements,
yesterday they were basically doing a back-handed slap
at Amazon sayin', "We're more open."
They did a deal with Mongo.
There's a lot of discussion in the software community
about how Amazon, obviously BullGuard's open source.
But, if you look, and some of that's true.
If you look at Amazon, they've basically taken
a lot of open source products and built their own databases.
But, if you look at Google, Google's got
relational databases, they've got non-relational databases,
they got operational databases.
And so, I wonder out loud, is this a Trojan horse strategy?
Because they need to own your data.
That database is so important.
Now the other thing I'll add is
I talked to Juan Loaiza yesterday,
who's a executive VP at Oracle.
And he said to me that the cloud providers
basically look at the database as another application
to run on top of servers and virtual machines.
He said we at Oracle, we integrate, you know they do
all the EXIT dative stuff, et cetera.
So, my point is, database is the war to be won.
That's where it starts.
And if you're gonna do AI, you wanna have the data
proximate to the application.
>> Well, I mean there's two ways to look at that, Dave.
I would say my take on the database war
or position in the stack is you look at it
from the old way or the new way?
The old way would be an Oracle, well,
we gotta preserve the database, we license it,
and we got all these license agreements.
The new way is to change the game of automation,
like what Google's showing, where all this stuff
is gonna be done on behalf of the customer.
So the business model of how databases
and the impact of data is being used will dictate,
in my opinion, the monetization.
And that's the question that everyone
that I've talked to on the show floor, offline,
on email, and direct message is
how are we gonna make money with containers?
How are we gonna make money with Kubernetes?
How am I gonna make money with data?
This is the fundamental question.
Now, if you look at the success pattern
of the partner ecosystem,
the money making is about new economics,
new price points, and new services.
So, if you're Deloitte or you're Accenture,
you're saying wow, if Google can automate all this stuff
that used to be really hard to do like data migration,
moving application workloads around.
That was once a high-profit yield activity
for the system integrators.
Or, selling databases, like Oracle.
That's the old way.
The smart partners are, instead of just saying,
"Okay, I'll take the new economics,"
where all that cost is abstracted away by the automation,
and I'll lower my price point, but still capture the margin.
The margin opportunity for Cloud is significant,
and this is where the smart money is going.
The smart monetization schemes are around leveraging
what Google and Amazon are doing at scale
and shifting their business model, take advantage
of the lower costs, but then lowering the price not as much
so they still capture the margin.
So, this is integration.
These are things that we're months and months prior to.
You go to data migration, Stu,
I mean those projects could be months.
So, smart money is saying, okay how do I make money on this?
It's not the old way.
So, there's classic, what side of the street are you on?
Old way or new way?
That's gonna define who wins and who loses in my opinion.
>> What do you mean by old way?
I mean it's who owns the license, right?
>> Selling the database license,
for instance, is an old way.
>> Essentially that's what Amazon does,
databases and service.
>> It's a license, buy as you go, but you don't have--
>> Oracle sells as a buy as you go, too.
I mean they could play that same game.
To me it's more about when it comes to database,
it's more about workloads.
How much of the world needs asset property databases?
'Cause that's Oracle's game.
Versus how much of the world needs less database,
data store for less-structured data?
And that's really, I think, what Google
and to a certain extent, Amazon, are betting on.
Although, both companies, especially Amazon is making a bet
on both transactional databases and non-relational.
>> In an ideal world, database would be free
and the margin get shifted to another spot,
that's not clear yet.
But still it can make money on database,
but it's a lower price.
So Google makes money on scale, so with Cloud's scale
they can lower the price of the database license
whether it's a service or some fee.
But it's the people implementing, like the integrators
and the people that are building applications.
As they build that agility in, how are they gonna monetize?
How does a company out on this floor make money?
>> I just remember data stacks, in like probably 2012,
I was talking to Billy Bosworth, the CEO,
about the merits of being in the AWS marketplace.
And he said, "You know, I'm a little nervous about that.
"What do you think, Dave?
"Do you think they're gonna own me at some point in time
"and compete with me?"
And that's what Google's announcement yesterday said
is you're our friends, we're not gonna--
they didn't really come out and say we're not gonna compete
with you, they just basically said we are more open
than AWS without mentioning AWS.
>> Yeah, so it's interesting.
You know I've only had a little bit of a chance
to walk around, but it's a different ecosystem than Amazon.
I remember six years ago, when we first went to Amazon,
it was game developers and all these weird startups
that I couldn't understand what they do.
And now it's like VM world, but bigger.
With just the broad ecosystem here.
You know there's a big section on collaboration.
I went to Enterprise Connect a couple of weeks ago
talking about contact centers.
You see a lot of the same companies here.
I heard Five9s mentioned on stage.
Zoom's here, how do they plug into Google Cloud?
I heard Salesforce talking about the modern contact centers.
So, it's a diverse ecosystem, but it's different
than Amazon and there's not, at Amazon there's always
that underlying thing.
Oh, is Amazon going to take over this business here?
You know I haven't heard that concern at this show.
>> Well, I mean look, the bottom line is that there's a shift
in the economics with this model of technology.
Back in the database question, the fact that MongoDB
was once forecast to go out of business,
oh, Amazon's gonna kill MongoDB.
They have DynamoDB, Google's got databases.
The fact of the matter is, there's no one database anymore.
Every application at some level has a database.
So, if you think about that, then you're gonna have
a new model where everything has a database.
And the database is gonna be characteristics on the workload
and applications, so I do agree with that point.
The question is, it's not mutually exclusive.
One database license for all, versus databases everywhere.
So, if databases are everywhere, then the connective tissue
becomes the opportunity.
That's where I think you see some of these data-playing
technologies with Cloud very compelling
because I can move data very quickly around
and that's where the machine learning really shines.
That's gonna be a latency question.
That's gonna be a data integrity question.
This is the new model, this is what horizontal scalability
means in the Cloud.
Not buy Oracle Database and we're good.
It's kind of that game is slowly moving into the diluvian.
>> Well, I think Amazon would say,
hey, if you're a database vendor, you gotta innovate
'cause we're not gonna stop innovating.
Whereas I think Google's message
to the database vendors is somewhat different.
It's we wanna partner with you.
And maybe that's 'cause they're not comin' from
a position of enterprise strength, but I'm sensing
two apparently different strategies.
I just don't know what the end game is,
and I believe that the end game is to own the data.
>> The tell sign on the database is the developer, right?
If I wanna run a document store because that's for my JSON
or my feeds if I'm using say a lot of JavaScript,
I'll use document store.
If I wanna use a relational database,
I'll use a relational database.
So, the ideal world does not have the developer forced
into a tooling and database decision that they don't want.
(laughs)
>> Yeah, but Mongo changed its licensing policy
as a direct result of what Amazon was doing.
So they made their community edition license terms
more restrictive.
I don't know if you follow that.
So, what they said is, any cloud service provider
that distributes our community edition,
has to open source their entire software stack
associated with distributing that or they gotta pay us.
So, basically saying you have to pay an open source tax
or you gotta pay us.
Very interesting change in their database strategy.
>> Well one of the announcements here on the day two
was the data fusion thing, which essentially to me
is a tell sign, as well, that fusion data, moving data,
integrating data is a critical thing for AI.
Machine learning and AI is only as good as the data
that its working with.
So if there's missing data, say in a retail transaction,
you potentially are missing out on an opportunity
to create a better user experience.
So, addressibility of data, having that accessible
is a critical feature for machine learning and AI.
And again, it's garbage in, garbage out relative
to the data equation.
High-quality data gets high-quality machine learning.
High-quality machine learning gets high-quality AI.
So, Stu, that's kinda what Cloud offers
with large compute, large horizontal scalabilty.
>> Well, and I said yesterday I was kind of disappointed
there wasn't enough talk about AI.
Well, Google certainly made up for that today,
didn't they, Stu?
>> Yeah, absolutely.
(laughs)
Sorry, was there a question for me?
>> What was your favorite keynote moment today?
>> Look, it was good when they actually let a couple
of the customers go up there and talk.
I was a little bit disappointed that some of the sessions
feeled a little bit too scripted for my take.
But they laid out a lot of pieces there.
It takes a little while to squint through
all of the adjustments and all of the changes
that they have there.
I'm still digging through, like on the Anthos,
we talked about it quite a bit yesterday,
but had some good conversations afterwards.
They've got the Cloud run announcement
that's coming out this afternoon.
But digging into that open source discussion
that you were just talking about from database
is something that I have a lot of interest in.
I'm glad we actually have Red Hat on today,
we'll get their opinion as to,
you know they know a thing or two about open source
and Kubernetes and how does something
like open shift fit with Anthos?
They can work together, but it's not a oh,
and everything works back and forth.
If I'm PKS, if I'm open shift,
or if I'm the GKE-based Anthos,
it's not seamless and it sure ain't free.
>> No, you're four in on customers though.
We heard from UPS, Scotiabank, Baker Hughes,
McKesson, we heard from Kohl's yesterday.
So, it's pretty high-level senior people
from the customer side speaking on stage, which is progress.
>> Yeah, the CIO of UPS I thought was great.
He really laid out the scale of their business
and how they grow.
>> All right, guys, we got day two kickin' off here
on the show floor here in San Francisco
for Google Cloud Next 2019.
And I've got all day interviews.
Day two of three days of live coverage.
Stay with us as we kick off a full day of great interviews,
executives, entrepreneurs, and ecosystem partners here
at Google Next.
Stay with us for more after this short break.
(techno music)