Intro

Mike Schwartz: Hello and welcome to Open Source Underdogs. I’m your host, Mike Schwartz, and this is episode 50 with Kathryn Erickson who helps lead open-source strategy at DataStax. Founded in 2010 and currently employing about 500 people, DataStax was one of the first and most successful companies in the Apache Cassandra big data Ecosystem.

Kathryn has an engineering background. You can listen to some of her great deep dives into the tech on the DataStax website. In her role on the strategy team, she’s helping to lead the company into its next phase of growth and community engagement. I hope you’ll enjoy this episode. And if you do, don’t forget to share a link on social media. You can find all the episodes on opensourceunderdogs.com, or you can retweet our announcement by following us on Twitter. Our handle is @fosspodcast. So, without further ado, let’s carry on with the interview.

DataStax Origin

Mike Schwartz: Kathryn, thank you for joining us today.

Kathryn Erickson: Sure, of course, thank you.

Mike Schwartz: Most of our listeners probably know about Apache Cassandra, one of the most popular databases for big data, but how did DataStax evolved in relation to the Cassandra project.

Kathryn Erickson: DataStax was founded by Jonathan Ellis and Matt Pfeil, both employees of Rackspace. Jonathan, being contributor to Apache Cassandra and Project Share as well, was considering leaving Rackspace, and Matt Pfeil went to talk to him and say, “Hey, there’s some really cool stuff going on here, you should really consider staying.” And by the end of the conversation, they were founding a company together.

And so DataStax was founded to support Apache Cassandra. Over time, we began adding Enterprise features and selling an Enterprise distribution of the database with these features added, and then, of course, more recently, the cloud platform as a service offering as well.

Evolution Of Support Offering

Mike Schwartz: Actually, I didn’t realize that you started out providing support. Because when I first ran into DataStax, I guess I had just known it as a distribution of Cassandra. And now, I see that you’re also providing support for the open-source distribution. Can you talk a little bit about how that’s evolved over time? Has it always been there or has there been a focus on for or against doing that?

Kathryn Erickson: It hasn’t always been there. When DataStax was founded 10 years ago, there wasn’t really a playbook for how to build and run a successful open-source company.
We were founded around the premise of providing support and consulting for Apache Cassandra. Over time, we did, all for the Enterprise Edition, but what you see with most Enterprises is that they have a mix of the Enterprise version and open source. For some customers, that’s dependent on the criticality of the data, and for other customers, it’s dependent on the features or the distribution, being the as-a-service offering or self-installed on-prem.

And so, what we saw in the last year was that there were some obvious things that we weren’t doing, and our customers needed support and consulting around open-source Cassandra. We are beginning to open-source a lot more of the features that would build Cassandra abundance, and so, it made sense to bring those offerings back.

Astra – DataStax Cloud Offering

Mike Schwartz: Okay, and you mentioned that DataStax launched a new hosted service called Astra. Do you see that product as a driver for revenue, or is it just an easier path for customers to test drive the product?

Kathryn Erickson: I think that will evolve over time. I think at launch, it is the easiest way to learn Apache Cassandra. And I think as we launched the hybrid option, I believe that’s later this year, that would become a more significant line of revenue.

Pricing

Mike Schwartz: Most of the revenue today I guess is from the license Enterprise product, so focusing on that, a lot of open-source businesses are moving towards consumption-based pricing. And I’m wondering, what kind of metrics do you use to determine what is consumption?

Kathryn Erickson: You know, a cloud-based offering consumption is based on
capacity. And with our licensed product and with Luna, the open-source support
offering, our focus this year has been around simplification of the pricing
model. And we revisit that each year.

With the Enterprise product, we previously charged for the Enterprise license, and then, an optional additional fee for advanced workloads, like Spark analytics and graph. That’s confusing for the customer, they just want a simple pricing mechanism. So, we collapse that pricing. And then, of course, for larger deals ,we would have ELAs, or special terms to accommodate those customers.

Mike Schwartz: That consumption is based on, like, per CPU, per server, or how do you actually figure out what is the size?

Kathryn Erickson: It’s true capacity-based, the size of the data set being stored. And as we move to Astra hybrid, which will be that offering on-prem, I think we’ll consider that pricing option there as well.

Market Segmentation

Mike Schwartz: Data persistence is like the most horizontal market on the planet. Every company basically needs to store data. When you can sell to everyone, it’s sort of a blessing and a curse. Do you segment the market at all vertically or by use case, or do you just not segment the market?

Kathryn Erickson: It’s hard to segment when you’re serving a pretty broad market. What we try to do is have as easy of an on-ramp for the different verticals as possible. We see data models look similar between IoT use cases, inventory and messaging data models would be similar.
So, we don’t segment the market for go-to-market strategies, but we try to find places of repeatable consulting efforts to speed up the successes for those customers.

Partnerships

Mike Schwartz: When you took on the role of director of strategic Pprtnerships, you probably did a survey of the range of partnerships that exist. Can you talk about like what is the partner landscape look like at DataStax?

Kathryn Erickson: I ran our technology partner program, and there’s two other sides of that, SI partners and the cloud partners. On the technology side, you want to make it easy as possible for customers to consume your product.

So, in a technology partner program, you want to
understand the user journey to get to your product, and make sure that those
adjacent technologies have the simplest most repeatable easy to build, easy to
test integrations as possible over time. If you want to think about specific
companies and integrations, every database needs an ODBC and JDBC connector.
And customers want those for BI, for reporting, for simple ways to move data in
and out of the system, but in the last few years, most customers also want to
see Kafka connectors and more high-speed ingest Pub/Sub integrations.  So, we want to accommodate those as well.

Mike Schwartz: Coming on the System Integrator side, you know, at Gluu, we found
that those have been essential for us, to be able to focus on innovating the
product versus getting involved in specific projects. But there’s such a broad
range when you’re serving a global market of the System Integrators. Do you
consider them channel partners or integration partners?

Kathryn Erickson: We usually consider them strategic partners when we take those types of partnerships on. And the goal is usually to help us penetrate markets that we don’t currently have field team in, or packaged, or cookie-cutter solutions. If you look at some of the stuff that we’ve done with VMware and with partnerships at Dell, we want to assert that the product stack works as recommended for customers that are used to seeing these reference architectures from these larger integrators and technology companies.

Most Important Partnerships For Driving Revenues

Mike Schwartz:  Which partnerships, do you
think are the most important for actually driving growth?

Kathryn Erickson:  Deloitte’s been in a role to our federal business, they know that space better than any startup could hope. VMware for helping to modernize Enterprise platforms. Enterprises that are looking at Cassandra and looking at DataStax are usually going through some type of digital transformation. And the product that they already have in place is VMware. So, everything that we could do to make that migration to know SQL smooth was helpful to those customers. VMware has been a pretty big partner in my journey.

Open Source Strategy

Mike Schwartz: Some of the companies
we’ve interviewed are moving to a 100% open-source strategy, specifically Chef
and Cloudera. In the past, the value property DataStax, it had improved
distribution of Cassandra.But do you see DataStax maybe moving more in
the direction of open-sourcing its platforms and some of that technology it’