Clint Sharp, CEO of Cribl, discusses the growth and success of the company. Cribl has experienced significant expansion over the past few years, with a hundred million in revenue, 800 employees, and 130% net dollar retention. The company focuses on helping customers manage their growing data through data movement, collection, and storage. They are planning to release a Lakehouse offering for real-time analytics. Sharp emphasizes the importance of data tiering and fit-for-purpose solutions in the IT and security data space. Customers are seeking cost-effective ways to retain and access data for regulatory and business needs. Cribl aims to be a critical infrastructure for telemetry data, providing value to customers by focusing on their unique data challenges. The company is looking to expand its product offerings and continue serving a large market. Sharp remains focused on customer needs and staying goal-oriented as the company grows. Cribl primarily serves large enterprises, including half of the Fortune 50 and 25% of the Fortune 500.
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Clint Sharp, CEO of Cribl, discusses the growth and success of the company. Cribl has experienced significant expansion over the past few years, with a hundred million in revenue, 800 employees, and 130% net dollar retention. The company focuses on helping customers manage their growing data through data movement, collection, and storage. They are planning to release a Lakehouse offering for real-time analytics. Sharp emphasizes the importance of data tiering and fit-for-purpose solutions in the IT and security data space. Customers are seeking cost-effective...Read more
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What kind of architecture are we talking about in order to manage the massive growth in data as we move towards 2035?add
What has been the evolution in data storage and management strategies over the past decade in order to meet regulatory requirements in a cost-effective manner?add
>> Hello everyone. Welcome back to theCUBE here. We are in our New York City, Wall Street, NYSC Studio, theCUBE East. I'm John Furrier, host of theCUBE + NYSC Wired and theCUBE. Working together, bringing best content here in New York, connecting tech in Palo Alto to money and business here in Wall Street. Clint Sharp, CEO of Cribl CUBE alumni. Clint, great to see you. Welcome back to theCUBE I said to the last guest who was on for the first time, but you've been on so many times. I remember when you guys started with the seed round.
Clint Sharp
>> Yeah.>> What year was that? That was like what? 2017?
Clint Sharp
>> We raised the seed in 2019.>> 2019.
Clint Sharp
>> Yeah, we've been at this for about seven years now.>> Well, first of all, congratulations. I want to get into some of the stats on the momentum. You guys have been growing so fast. We've been following the rise again last time year around, we talked about it, tons of momentum. Give us the quick numbers, momentum, size, revenue, employee growth. Give us a quick update.
Clint Sharp
>> Yeah, so about 15 months ago, we announced that we were at a hundred million. We're growing at about 70% year over year. So it's truly, truly massive growth. We're getting close to 800 employees, 130% net dollar retention. That just showcases the value that we're providing to customers that it's not only do they buy, but they continue to grow and expand because of the value that we provide.>> I remember our first time on theCUBE when we talked about Cribl. I'm like, oh, wait a minute. At that time, it was just like Splunk. You had data pipelining. Data analytics was hot. It was a big market. But then we had talked about the future of data. I think you might have... We didn't say AI, but we said there would be a tsunami of data. Talk about the impact, how analytics has changed just from a pure data acquisition, data management. Just the velocity of data now with AI, you don't have real time data. You don't have the horizontal platforms. You don't have the ingestion. I mean, data movement was one thing at the beginning. Now it's turned exactly as we talked about. Back in 2019, it was like, yeah, that could happen. It did. Take us through to what actually happened and how that propelled you guys.
Clint Sharp
>> So I mean, look, customer's data is growing at a 28% compound growth rate, and I've asked thousands of people this question, is your budget growing at 28% and not a single persons is. And so that means that what got us to 2025 is not going to get us to 2035. What kind of architecture are we talking about? How are we going to manage this massive growth in data? We started in streaming, and we started helping people create a diverse tiered architecture for their data. So now I put it always in the most expensive destination. Let's create a lower cost destination where this data can go, a data lake where we can store that data cheaply. And that vision's been realized, and we've started to expand beyond just data movement into data collection. We have our product edge, we have a product lake that allows you to store data. And we have our product search that allows you to federate that query into a bunch of different engines. And we're super excited because this year we're going to announce our Lakehouse offering, which is going to give you real-time analytics on top of Cribl Lake to give you very fast query over petabytes of data at rest. And so Cribl has just continued to expand, but always complimentary. We're always working with other vendors. We're not looking to go out and replace anybody else. We're just looking to give our customers more options for their data management than they had before.>> At that time, you mentioned streaming. At that time, that was hot, obviously everyone was streaming. And then I talked to the Uber guys. They built their own streaming. I think they ended up using a bunch of different solutions, but the discussion at the time was it's just, it's a feature, not a company. You guys saw that aperture and innovated in other areas. You mentioned the tiering. As AIs here, what is the innovation strategy for Cribl to have a portfolio of offering? Because data tiering security is a huge issue. Right? AI's going to help the security market. You got coding, you got all kinds of data enable value, where streaming is inherently there and a bunch of other things. What are the key things that you're doing that are going to be key architectural building blocks for this next wave of apps? There'll be agentic of course and other things coming, but if you don't get your data in order, those agents don't work.
Clint Sharp
>> Well, exactly. So I mean, as we've always said, it's better to sell pickaxes to miners than to try to be the person who's helping them harvest the gold. Right? We think that there's a huge opportunity to continue to be the infrastructure for people in this wave of AI. And if you think data is growing fast now, now let's glue up a bunch of AI agents which are now producing at way faster than human speed these massive amounts of interactions, which is just going to cause way more telemetry data to spew off. Every time an agent's interacting with a system and they're doing it now way past the speed of human thought, the amount of data growing is just going to be hugely massive. And then we're also going to need smart, intelligent analytics systems to help us make sense of all of this data. So we've launched our co-pilot in the last year. We'll have some great new innovations this year around helping people deal with... One of the hardest problems when analyzing data is kind of that blank sheet of paper. Like, hey, okay, well what questions should I even ask? What do I have? What am I supposed to even do with this pile of data that I have? And so having AI agents that are capable of looking at this data and giving you suggestions along the path that you should work is going to be a huge area of investment for us.>> Yeah. And I think that brings up the whole business value. One of the things we've been riffing on, our last event we did here and in Palo Alto was around CFOs. And it wasn't about CFO how to do finance, it was more of how do you run your financial strategy now that data is a critical element? And the number one thing, Clint, that came out of that conversation was it's business transformation is coming fast, not IT transformation or digital transformation, that the business models were evolving. And a lot of the questions that they're asking, I'd love to get your take on this, is we don't even know what we can do yet. So first thing is what do we got? What can we innovate? What's in front of us, and what don't we see, that clean sheet of paper so to speak? So you're seeing this whole business transformation, so they know there's gold in those hills, okay, but they have maybe one pick and shovel today, but they don't know they might need something else. What's your take on this? Because you talk to a lot of customers. What are they thinking around this next wave? Well, first of all, do you agree on business transformation? And two, what do they need to do to prepare to even know what's a business opportunity?
Clint Sharp
>> For sure. So I mean, I think for our customers, we sell to the people who run the systems who run the business. So I say a lot like, when's the last time you thank the guy running your email? Right? It's the kind of grisly-haired systems administrator sitting in the basement. And so as these businesses are transforming, suddenly people, if they were an offline business before, they're an online business now. So being able to understand the performance of their systems has a meaningful bottom line impact. Being able to understand the security of their systems has meaningful bottom line impacts. And so the information technology and security departments are suddenly becoming significantly more mission critical than they were. And so that's what's really I think important for our buyers is they're looking at it... Their bosses are no longer tolerating downtime. They're no longer tolerating security breaches. They're so business critical. And that's really the class of data that we're helping them with. And it's a huge, huge problem for them.>> It's interesting because when shit hits the fan, they're the first ones gets the call, and when nothing's happening, they just can have a normal life. The love is peace, right, when nothing's broken, right?
Clint Sharp
>> The best case you get is this, that your boss is not yelling at you. They're truly an underappreciated persona.>> One of the things that I'd asked this guy who was platform engineer. I said, "Hey, AI when it helps automation, what's the main benefit?" And the direct quote was, "I get more beer time." And that was a proxy for hanging out with his friends and that was what he saw as value, not coming in on the weekends or doing the things that you got to do when there's disruption, operational disruption.
Clint Sharp
>> We hope we let our customers go home a little bit earlier, right? Spend a little bit more time with their family. Maybe it's beer time, whatever their recreation of choice is.>> Family time, beer time, whatever they want. Beauty's in the eye of the beholder as we say. Okay, so talk about the questions you get customers. You mentioned the question you asked early on was, "Is your budget growing as fast as data?" And the answer was no. Click, check the box, all steam ahead, burn the boats, go after the opportunity. You're here. You're in a much different place now than you were then. What questions are you asking customers and what are they telling you? What's the big pain point? What's the big ask that you guys are evaluating leaning into from the customers?
Clint Sharp
>> So it's mainly around their data retention right now. So it is they're being mandated by regulators to keep this data six, seven years. How do I do that cost effectively? And then how do I maintain access to that data even though it's been online for that long? And how do I do that without breaking the bank? And so if I'm doing it in the solutions that I've had for the last 10 years, you're talking tens of millions of dollars to store, retain, query, analyze this type of data, and they're being told by their regulators, "Well no, you have to have more. You need another two years worth of data. You need another five years worth of data." So how do I even keep that and still make that accessible? And so we believe that we can bring an order of magnitude more data for the dollar by using new cloud-native techniques. And that's really where we're seeing the huge lights go on for our customers is that like, oh man, so I could retain this data just like my regulators are saying I have to retain this data, oh and I can also make that data accessible so that when they come by and say, "Hey, can you go back two years and look and see whether this person talked to this person on those devices and the light bulbs just go off.">> You guys, would you consider yourself critical infrastructure for data then? What category... I mean, it's hard to put you in a bucket right now. What category, how would you peg your category?
Clint Sharp
>> We're telemetry data. And so there's a lot of general purpose data analytics companies out there. And this market really requires fit for purpose because the type of data that we analyze, it's ugly, it's nasty, it doesn't fit neatly into rows and columns. It's not spreadsheets, it's log data, it's data that's mixed text and it says John logged... Literally the thing says John logged into his device. Okay, well that's important timestamp. Now I know John logged in, but it doesn't fit neatly into databases. And so we really focus on IT and security data very specifically. So we say we are the data engine for IT and security.>> It's hard because telemetry could be broad stroke category, but you're deeper than that. I mean, you're deeper than telemetry though. You're doing a lot of stuff in there. Intelligence, data tiering, what's the secret sauce if you had to?
Clint Sharp
>> It was building this engine from scratch to focus on this data for this particular persona because... And we look at companies like Snowflake and Databricks and these guys are amazing, amazing companies, but the type of software that they're building isn't built for the people that we sell to. So investing in this engine that focused directly on them, giving them the ability to route it, analyze it, be able to store it, retain it, all of that together solves their full data management challenge.>> Yeah, a great business strategy and again, really, really proud of you guys watching you guys grow. It's fun to see the massive growth as you focus on a problem, own it, own the persona, own the beachhead, dominate it, keep innovating. I guess the next question is what's next? What do you guys sequence to as you go to the broader market opportunity? At some point you'll saturate that TAM or you're pretty much happy and content now.
Clint Sharp
>> So as we move into storage and analytics, John, being able to store... Before we were a data movement company and the TAM for that is a certain size. I think we are lucky to be one of the few companies that I know of where our second products, so our search and lake products have such a much larger TAM than our streaming product that we think the future is bright on what we've already shipped. And then we have other products in the pipeline as well, which we'll continue to grow and expand that.>> So you think you got a lot of TAM left on the new product?
Clint Sharp
>> Yeah, absolutely. And so with our Lakehouse offering as well that I mentioned earlier that's coming out in February or March timeframe, that expands us from sort of archival analytics into real-time analytics, which gives us way more use cases that we can go address.>> Yeah. And one of the things you guys really address out of the gate and continues to be core is the pricing, the value to the customer. Can you talk about data tiering and why that's important to that? Because I think data tiering, you mentioned it earlier, is a big part of this. What does that mean for enterprise and how does that render itself into a value proposition that's not going to break the bank to use your words?
Clint Sharp
>> Yeah. And so I think if I look back and I've been... I think the first time I met you was a decade ago when I was at my last job. I think we all thought that we would get a system that would own all this data. And I'm just going to pour it all in there and then awesome. But I think what has happened over the last decade is we've realized that there isn't a one-size-fits-all approach. I can't just put all of my data into an indexing solution or all of my data into a time series database. It doesn't all fit there. I need a data lake, I need some streaming solutions, I need some ability, I need a Lakehouse type of solution. And so really being able to put the right data in the right place is what's finally making it cost-effective for people to meet these regulatory requirements, these observability requirements that they have. And so creating a portfolio of products is really where we're seeing these enterprises go. I think people think consolidation, but really the reality is that they end up building best of breed because their requirements are unique enough that they know they're going to need a variety of places where this data goes. And Cribl is uniquely positioned to help them build that portfolio.>> Sometimes you've got to consolidate to handle the growth. Otherwise it's broken. Final question before, I know we got a break here, but I really am curious as founder, lead entrepreneur, and you've got a great team, you guys are growing like a weed as CEO founder, you're at a level now that is pretty massive. You're at the peak of what ground zero, start zero to one, one to a hundred million plus in revenue. As the founder and CEO, what's it like to be where you're at right now because you've got a great business, great tech team, you got to go to these Goldman Sachs conferences, money's coming at you like crazy from the capital markets. We're in New York, obviously you're not public yet. You could go public. I mean, you got the team getting off site coming up. What's going on as the founder and CEO? This is what you dream about. You're at where you're at. Where you are now, it's not where you were, you're at a different place. What's it like?
Clint Sharp
>> I mean, I get the question a lot and I don't think you can ever really... Sure. I mean, we joke my co-founders and I, that going back into JIRA and put a ticket in there and that says that we planned exactly all of this way. We didn't. We've been very fortunate. I think we had the right solution at the right time. What's it like for me? In my mind, still very similar to what it was seven years ago, which is stay really focused on goals. What are we going to achieve? This multi-product goal for us is really important this year. Continuing to grow. This year we'll grow probably another 55%. And so just stay maniacally focused. But most important to stay focused on the customer, put them first and the rest of the things take care of themselves.>> How's the customer base doing, mix of business? How would you break down the customer mix?
Clint Sharp
>> Yeah, so we are primarily in the upper end of the market. So we have about half of the Fortune 50 and about 25% of the Fortune 500. So that's kind of where we are focused today is large, large enterprises in their most pressing challenges. And I like that because I come from large enterprise backgrounds, and I just really empathize with the problems that they have.>> Yeah, yeah. Well congratulations, Clint. Great to have you back on theCUBE. Thanks for coming in.
Clint Sharp
>> Thanks, John.>> Not too shabby the new set here.
Clint Sharp
>> I'm loving your set, John. This is so, so cool.>> We got the other set over there in the button room coming online soon. Great to have you. Congratulations, and we'll talk to you soon.
Clint Sharp
>> Thanks John.>> Sure. Okay, this is theCUBE here in the Cube East. This is the NYSC CUBE Studios, the CUBE and the NYSC Wired Media Week as part of NRF big retail event. AI is obviously everything. Data is driving all the value proposition and Cribl is really leading the charge there, making sense of it and making telemetry work. I'm John Furrier, your host. Thanks for watching.
