DAIN HANSEN: Hi.
I'm Dain Hansen, Director of Product Marketing
for Data Cloud at Google.
I'm excited to welcome David Meyer, Senior Vice President
of Product at Databricks.
I'm joined also by my co-host today, Nicole Mackenzie,
who helps lead partner marketing for our Data Cloud group.
David, it's great to have you here today.
DAVID MEYER: Thank you, Dain.
It's great to join you for the Google Data Cloud Summit.
NICOLE MACKENZIE: Yes.
Welcome, David.
I know the three of us have had the opportunity to watch
the partnership grow since the beginning
when we first launched.
And it's amazing to see where we're at today.
DAIN HANSEN: Absolutely.
Databricks is one of the most exciting data and AI companies
right now.
And, David, you've been at Databricks
for nearly five years, and we've been working together
on Databricks since the launch on Google Cloud just
a little over a year ago.
Let's start with some of your recent observations
about why there is so much interest
in Databricks on Google Cloud.
DAVID MEYER: Yeah, absolutely, Dain.
So I think Google's always been known for its technology.
And engineers have been drawn to working
on Google Cloud because of the fundamental technology there.
And similarly, Databricks is known
for its technology and the technologists at Databricks.
So there's a lot of shared cultural heritage there.
So when Databricks was coming to Google Cloud,
people were excited.
And customers have been asking for this,
to be honest, for the five years I've been at Databricks.
So there was a lot of anticipation.
And then the ability to leverage this open source core
capability to run all of your data and AI
on these combined systems, well, customers want it,
but they also need it to achieve their goals.
So I think there's been a lot of interest.
It's been a very exciting year.
NICOLE MACKENZIE: That's fantastic, David,
and it has been a pleasure to work with you.
So let's talk a little bit about the integrations
that Databricks has with Google Cloud.
Can you share a little bit with us
how Databricks and Google Cloud are partnering together?
DAVID MEYER: Yeah.
So I talked about the data and AI
coming together in this open lakehouse and the open source
foundation of it.
So customers are coming to this because they
need to operate on all of their data as it's coming in
and as it is being modified and do the data science
and machine learning directly on top of that.
So Databricks operates on the Google Cloud
that customers love.
And it makes the value in it higher.
So basically, when people are managing their data
in Google Cloud Storage, all of their data storage,
or in BigQuery, and then orchestrating it
with Google Kubernetes Engine, Databricks
runs on that infrastructure.
So what you have in Google Cloud, we leverage that
and we make it more powerful.
And then the Google tools like BigQuery, Vertex AI, and Looker
for the different types of engineers
to operate on that data, those all plug natively in.
So you use the tools in Google BigQuery and Google Cloud,
and then the Databricks lakehouse environment
based on standards just layers on top of it
and you can use it all together.
And that's what customers love.
DAIN HANSEN: Hey, I love this lakehouse approach, David.
And I love that we're working together
on connecting these open standards in such a way that
gives more flexibility and extensibility to our customers.
And it's great to see you're using
our cool products like BigQuery, and Vertex AI, and Looker--
and, of course, running it on Kubernetes.
So thanks for all that.
But I think also we see so many of these integrations come
to life with our customers.
And through this partnership--
I know we've collaborated on a lot
of these different partnerships, now
we're starting to see customers apply these in the real world.
Do you have any examples you can share with us today
on some of these cool examples?
DAVID MEYER: Absolutely.
Let me first take a step back.
So data and the AI that derives insights from it
is the lifeblood of the modern company.
All industries are transforming themselves around data and AI.
So we have a mutual customer-- it's a Fortune 500
logistic supply chain customer.
So imagine running a supply chain
in the last couple of years.
It's bonkers.
COVID disrupted everything.
There was all kinds of massive changes
that affected your supply chain.
So in the old world, you had kind
of a data stack on one side and an AI stack on the other side.
And you are preparing all of your data,
managing all of your data, and you
might get it cleaned and updated once a day.
Then you try to bring it over to the other side of the stack
and get insights through machine learning and things like that.
You can't do that anymore.
You have to have real time insights.
So bringing this data and AI together into this lakehouse,
all sitting on top of GCS, all of the sensor
data in the supply chain and the IoT data
can land right in the lake.
And the machine learning and AI can happen right on the lake.
So instead of what this company was
doing before was they had a daily refresh of the data
they operated on, now, they have real time, continuous insights
into the data coming in from their supply chain.
So there's a problem at 9:00 AM, they can act on it at 10:00 AM.
And that's necessary in today's world,
as hyperdynamic as it's becoming,
and the supply chains have to adapt.
So that's what customers are able to do
bringing the Databricks technology on top of GCP.
NICOLE MACKENZIE: What an amazing example, David.
I love how we're working with customers.
And one of the customer trends we are observing
is the growing adoption of leveraging a simple and open
approach to analytics and AI in one place,
on top of the data lake.
Are you seeing similar patterns emerging?
DAVID MEYER: Absolutely.
I think the openness is core.
The stacks of old, they locked you in.
And then every 10 years, you had to re-platform.
But if your whole business is running on data and AI,
you can't fall into that trap again.
So bringing data and AI into this common lakehouse that's
based on standards-- basically, together, Databricks and Google
have to earn your trust in business every year,
or else you can just take your data into another system.
So that's how we have aligned incentives with our customers.
So there's a US grocery delivery service,
and they were able to bring all of this data.
And Databricks has a specialized connector into BigQuery,
so we can dig into BigQuery, and push down queries and things,
and take all of that data, and do machine learning directly
on top of it.
So when you add those performance capabilities
and not having to move the data around,
this delivery service was able to basically 10x
their performance.
The job that took 10 hours, took one hour--
specifically, they could improve the performance 750%.
Now, since a lot of the consumption-based cost
is on this performance, they were
able to reduce their costs by $300,000 a year
for the first use case they brought into this platform.
So their performance dramatically increased.
Their costs dramatically went down.
But what's even more important is now they can do more.
They can do things they couldn't have
done before because of the limitations of the system.
And the open source capabilities means
they can plug all of their data engines
into this same platform-- the Databricks
on top of Google Cloud.
So those are the things they're able to do when they
bring everything together into one system based
on open standards.
NICOLE MACKENZIE: Super impressive,
and just another example of how we're partnering together
with customers.
On that note, thank you, David, for joining us today.
Together, we are excited to deliver such a strong business
value to customers.
So any final thoughts?
DAVID MEYER: I mean, first of all,
thank you to the audience for being here,
to Nicole and Dain for doing this with me.
The thing I'm most excited about is that we've just
scratched the surface.
We're just beginning.
So everything we see customers doing--
we see industries transformed across every kind
of capabilities we see--
that's just maybe 1% of what's possible
and what will be happening in the next bunch of years
as we bring the technology of Databricks
together with the technology of Google
Cloud and this open system to do data and AI together.
So I'm just super excited to hear the rest of the content
today and to see what these customers do
over the next bunch of years.
DAIN HANSEN: This is awesome.
Thank you, David.
Thank you, Nicole.
And thank you for joining the session today on the Data Cloud
Summit.
I'm so excited about what we've discussed about the Open Data
Cloud on Databricks-- so many great things
that we're doing together.
And it's just great to see the synergy between the two
companies.
So once again, thank you again, and we'll see you next time.
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