The following is excerpted from the question-and-answer section of the transcript.
(Questions from industry analysts are provided in full, but answers are omitted - download the transcript to see the full question-and-answer session)
Question: Kasthuri Gopalan Rangan - Goldman Sachs Group, Inc., Research Division - Analyst
: Congrats on the quarter. I just want to clarify the seasonality comment, Michael, that you made with respect to Atlas. So we're merely
talking about it sequentially only because Atlas is a much larger business today than it was exactly a year ago going into Q1. Or are
we actually calling out any structural changes in consumption that underlie that forecast? I also have a follow-up question.
Question: Kasthuri Gopalan Rangan - Goldman Sachs Group, Inc., Research Division - Analyst
: Got it. So consumption as a structural change driver of your Atlas business is still as positive as you felt...
Question: Kasthuri Gopalan Rangan - Goldman Sachs Group, Inc., Research Division - Analyst
: No change. Got it. Yes. And one for Dev. When you look at the cohort of Atlas customers initial deployment, it's definitely small, but
then what are some of the bigger deployments on Atlas looking like that rival, the more traditional on-prem deployments that give
you the conviction that some of the biggest database deployments on the planet could end up being completely cloud native and
might -- the prices 2 to 3 years from now?
Question: David E. Hynes - Canaccord Genuity Corp., Research Division - Analyst
: Nice set of numbers here. Dev, we've seen a bit of an inflection in revenue per customer over the last couple of quarters. I'm wondering
if that's more a function of your big customers getting bigger, right? I mean, we saw a record $100,000-plus adds. Or is it all the
smaller starting Atlas customers that you've added over the last couple of years now kind of ramping to more material spend levels?
I'm sure it's a bit of both, but I'd love to get some qualitative color.
Question: David E. Hynes - Canaccord Genuity Corp., Research Division - Analyst
: Yes. Okay. And then Michael, my follow-up for you. I mean, obviously, the EA strength in the quarter drove the strong cash flow that
we saw. As you look out to fiscal '23, do you think Mongo can be free cash flow profitable?
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MARCH 08, 2022 / 10:00PM, MDB.OQ - Q4 2022 MongoDB Inc Earnings Call
Question: Karl Emil Keirstead - UBS Investment Bank, Research Division - Analyst
: Maybe 2 for Mike. Mike, back to the Atlas strong sequential usage growth, I'm sure you're well aware that some of your peers,
Snowflake, Confluent, Datadog, that also have AWS-centric usage models called out a bit of a usage lull or unusual consumption
seasonality in December, January. Did you see that?
And if you -- and perhaps it was offset by other drivers? Or did you not? And if you didn't, what makes your model different from
those peers?
Question: Karl Emil Keirstead - UBS Investment Bank, Research Division - Analyst
: Yes. Okay. That's perfectly clear. And then my follow-up. I just want to be crystal clear on what you're conveying when you say that
you're not assuming a pandemic impact in your fiscal '23 guidance, Mike. Are you really saying that you're guiding less conservatively
going forward and, therefore, implying that perhaps we should not be thinking that the beat cadence will maintain at the level
you've put up in the last 2 to 3 quarters?
Question: Rishi Nitya Jaluria - RBC Capital Markets, Research Division - Analyst
: Two -- just 2 on my end. First, I wanted to start with the serverless offering, which is in preview mode. Can you talk a little bit about
how has customer feedback and early adopter feedback been? How to think about the long-term impact if this starts to see real
adoption? And maybe help us understand some use cases that you've seen for serverless versus the core Atlas? And then I've got a
follow-up.
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MARCH 08, 2022 / 10:00PM, MDB.OQ - Q4 2022 MongoDB Inc Earnings Call
Question: Rishi Nitya Jaluria - RBC Capital Markets, Research Division - Analyst
: All right. Great. And then I wanted to go into the NRR. Showing 120%-plus NRR at $1 billion and ARR is really impressive. Can you
talk a little bit about what are kind of some of the drivers of being able to maintain this level of NRR at this scale? Is it a function of
expanding workloads, new use cases, upmarket momentum, lower churn? Maybe walk us through a few of the drivers for keeping
it up and how to think of that metric going forward.
Question: Steven Richard Koenig - SMBC Nikko Securities America, Inc., Research Division - Analyst
: Just one question today from me. Last week, it was pretty surprising to see from Snowflake how performance improvements in their
platform negatively impacted effective pricing and the revenue outlook. And I don't think I've ever seen that, either working in or
covering database companies. And so I'm wondering, without commenting on them, tell me about maybe your model. Why won't
performance improvements negatively impact you guys? And is there a difference between operation and analytic data stores that's
relevant here?
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