Michael Gordon: Sure. Yeah, just quickly in linear, I don’t think there’s anything particularly point out of note there.
Dev Ittycheria: And so regarding Vector Search, and I’ve shared this with other — talked about this previously, Vector Search is really a reverse index. So it’s like an index that’s built into all databases. I believe, over time, Vector Search functionality will be built into all databases or data platforms in the future. Yes, there are some point products that are just focused solely on Vector Search. But essentially, it’s a point product that still needs to be used with other technologies like MongoDB to store the metadata, the data to be able to process and analyze all that information. So developers have spoken loudly that having a unified and elegant developer experience is a key differentiator. It removes friction in how they work.
It’s much easier to build and innovate on one platform as learning and supporting multiple technologies. And so my strong belief is that, ultimately, Vector Search will be embedded in many platforms and our differentiation will be, again, like it always has been a very compelling and elegant developer experience.
Michael Turits: Thanks, Dev and Mike.
Operator: Thank you. And one moment for the next question. Our next question will be coming from Mike Cikos of Needham. Your line is open. Mike Cikos of Needham, your line is open.
Mike Cikos: I’m sorry. I apologize, the operator [indiscernible] Thanks for getting me on the call here, guys. If I could just follow up on, Dev, your comments there in response to Michael on the Vector Search. I know that we’re talking about the developers and how they they’re voting here because they want the data in a unified platform, a unified database that preserves all that metadata, right? But I would think there’s probably also a benefit to having it all in a single platform as well just because you’re lowering the TCO for your customers as well, right? They’re not paying a tax for the movement or duplication of all that data between different vendors. Is that also a fair assumption when I’m thinking about the potential that you guys bring versus maybe some of those more point features or databases out there?
Dev Ittycheria: Well, with vectors, vectors are really a mathematical representation of different types of data. So there’s not a tonne of data, unlike application search, where there’s a profound benefits by storing everything on one platform versus having an operational database and a search database and some glue to keep the data in sync. That’s not as much the case with Vector because you’re talking about storing essentially an elegant index. And so it’s more about the user experience and the development workflow that really matters. And what we believe is that offering the same taxonomy in the same way they know how to use MongoDB to also be able to enable Vector Search functionality is a much more compelling differentiation than a developer have to bolt-on a separate vector solution and have to provision, configure and manage that solution along with all the other things they have to do.
Mike Cikos: Got it. Thank you for helping clear my understanding on that. And then just a quick follow-up for Michael. Michael, I’ve gotten a couple of inbounds just trying to unpack the Q3 revenue guide here, specifically as it pertains to Atlas. And I think what people are looking at is, I think Atlas embed slower sequential growth on a daily consumption basis. The questions I’m getting are, was there anything onetime 2Q that would cause us to think that the daily Atlas consumption growth would decelerate going into 3Q? Or anything else you can tease out there while we have you?
Michael Gordon: No. I think if you look at what we said is the real underlying reason for the increase, obviously, we don’t guide by product, but we are trying to give you a whole bunch of color around it, the real increase — and the Atlas number is given the slight outperformance in Q2, we have a starter hiring ARR in Q2, and that’s at the beginning of Q3. And that’s really what’s flowing through in the numbers and in the guidance.
Mike Cikos: Terrific. Thank you very much guys, I appreciate it.
Dev Ittycheria: Thank you, Mike.
Michael Gordon: Thanks, Mile.
Operator: Thank you. This concludes the Q&A session for today. And I would now like to turn the call back over to Dev Ittycheria, CEO, for closing remarks. Please go ahead.
Dev Ittycheria: Thank you, everyone, for joining us today. I just want to reinforce that we had another strong quarter of new business performance, which really validates our value proposition and our run anywhere strategy. Again, we remain focused on our North Star, which is acquiring new workloads, both from new workloads — new customers and existing customers. And we’re innovating both on the product and go-to-market dimensions to accelerate workload acquisition. And while it’s early days, we believe that with the rise of AI, MongoDB will be a beneficiary of as AI becomes more prominent. Thank you very much, and I appreciate all your time. Take care.
Operator: This concludes today’s conference call. Thank you all for participating and enjoy the rest of your evening. You may now disconnect.
