MongoDB (MDB) 5 Dec 232024 Q3 Earnings call transcript

Thank you for standing by, and welcome to MongoDB's Q3 Fiscal Year '24 Conference Call. [Operator Instructions].

As a reminder, today's call is being recorded. I would now like to turn the call to your host, Mr. Brian Denyeau from ICR. ahead. go Please

issued Valerie. us you, XXXX and you press thank Results, market of Great. today. to Good review joining release our in today we Fiscal the MongoDB's for close which the Thank announced afternoon, at Third Financial Quarter

the are me MongoDB; President of Dev and on Joining Michael CFO. Gordon, Ittycheria, CEO and MongoDB's call today COO and

our to subject planned investments. conditions These product a to make our differ risks statements we our results and results and future this will are and forward-looking the uncertainties, financial the statements, of materially our benefits statements operations guidance opportunities, to including from of call, expectations. customer cause of could and that variety market landscape, related our platform, future competitive financial behaviors, growth During including our our

For the a XX, filed required on risks on affect obligation views ended the uncertainties made our to our that in quarter XXXX. this X, today results, on and Form our could risks SEC law. the please except September quarterly that report was refer for described Any reflect discussion statements as them, actual material as XX-Q XXXX we of update forward-looking undertake call to of and no by only the with July

a our for discuss measure. release website on financial measures we Please Relations most of on in of directly financial the to non-GAAP their our tables earnings GAAP Additionally, refer the will this these conference to comparable call. portion measures Investor reconciliation

to turn the With over call Dev. like that, to I'd

giving that continue market by a I execute broader update. today. strong joining we well despite I'm before third you start company you thank and we Thank to you, Brian, for everyone will our results as us pleased another report quarter had reviewing challenging conditions. to to

quarter total million increase of grew revenue. our growth, year-over-year, representing Overall, margin, XX% the the guidance. $XXX of of revenue with and a XX% XX% solid XX% quarter of operating customer non-GAAP non-GAAP year-over-year QX. generated had income another a customers. $XX We operating ending revenue Atlas strong of above XX,XXX We million, an for we generated high delivered and we end over

We had by led within workload continued business existing quarter in of new customers. healthy a acquisition acquisition strength our new

In exceeded expectations the addition, strong and run for platform appeal anywhere Enterprise our strategy. of Advanced our business our again demonstrating our demand

Moving with in on trends. later. consumption line Michael consumption trends our to will quarter more Atlas played The discuss in out detail expectations.

mission of in Finally, retention rates the criticality environment. reinforcing even a our difficult platform remained spending strong QX, in

most This share Board industries various and our C-suite together From quarter, recent these and to meeting, across feedback where we few customers, with our emerge. themes our dialogue held well a the experience came using Advisory ongoing MongoDB. about global discussions as insight geographies as Customer customers

is Copilot in from sizes. seeing generating AI on MongoDB's early on with partnership in years reflect companion practices suggestions generate proficient faster First, great also of code that coding is the applications build performed best to GitHub on data CodeWhisperer, to every MongoDB nearly feedback now code trained We're conversation is customers AI-powered with of our all AWS' from MongoDB. developers history. best practices that XX Microsoft suggestions highly based even over at aiding

experts. the to being the Increasingly, longer AI, their powerful with are AI domain directly into asked software is Gen sole And advances no who recent applications. applications AI build developers building in functionality it's AI/ML of

well-positioned are them just help to do that. We

organizations to the to private and or accuracy search use we vector exceptional can availability the data RAG, their generation retrieval from use public Customers LLMs. leverage building preview, interest in announced our are where of yesterday. cases general AI search a increase range saw We of semantic of augmented

plus XX,XXX human employees, people a UKG, Atlas leaders. customers' that over globe chose their around Vector guide customers Search managers technology workflow serves HR assistant an use example, helps for For AI-powered the capital and to MongoDB and management

They changing to chose large not because added of as Atlas state Score received Vector recent developers databases and search rapidly the data to of AI is reported scale handle by the all a evolve to Vector workloads. compared applications survey UKG highest the Atlas available flexibility Net its in retool, alone. market. architectural minimal complexity, In far by vector Promoter Search from handle other

namely Vector-based query capabilities powerful can queries provides developers tech series. with Moreover, provide. additional and filters just Vector of solutions other Search MongoDB on that analytics, geospatial cannot search, available combine other This ways any in time defining

Or pants, top-rated you look this find schools. in can and like in years are estate image the have with queries downtown with real AI houses rich my within within and this built like in shoes that and miles X were listings range For of a west that run size example, price shipping. X particular the a outfit last find complex shirt, Chicago image in look such as area free an that

aware building They more for platforms feel applications customers that data modern modernize to ever Second, are designed pressured an future. AI holding legacy are their them their than infrastructure. back from

they a process However, as the technology, customers modern, customers that are also the us Consequently, complex tell people. increasingly capacity looking successfully. aware MongoDB modernize them skills and are to endeavor modernize. challenges involves become all lack by but to it's help They that want are to the and they to daunted

Relational Migrator year successfully MongoDB. migrate to their launched data help legacy customers earlier from We this databases to Relational

looking to analyze and procedures to the event, beyond migration AI which queries Query MongoDB's Converter, application we're data API. full Generative uses SQL work local with and London to them unveiled store existing life the our convert cycle Query of Now modernization. we At

to need procedures successfully changes. decades-old modernize their convert already Customers minimal with tooled manual back-end to for

invest goal in AI still other the the significantly MongoDB. to While the with in applications run it's on to monetizing days, reducing Converter effort early continuing Query features we're of and involved legacy

our time ramp, take largest growth to will but business. is modernization opportunities the of application clear, be one To for long-term

strategy than conflicting way the run differentiator real movement to and continues appreciate to Third, they the On platform the the greatly as Customers continues cloud. in customers optionality on the maintaining anywhere the our are a to industries migrating nimble that financial cloud, were geographies priorities move to be manage one to cloud urgency unabated. reduce now first our hand, provides as cost hesitant as to customers them on-prem in the costs. often more that Southern the legacy to to moving is services become our the and Europe such cost of cloud all-in Many with of to workloads cloud. higher the of find

existing existing they our to a building new demonstrates are meaningful to on-prem foreseeable to modern run our the footprint to keeping anywhere maintain ability customers a their tell include infrastructure the the move for and customers keep eventual outperformance they In requirements, want of meantime, using platform future. of of regulatory planning apps cloud. to The EA The future-proof business reasons On the the other and EA. to enormity to on still task hand, or our for data largest deploy enterprise migrating on-prem by on-prem applications. their all desire us continued the the workloads that their our value cloud

use productivity on more variety with solutions. need vendors by focused of architecture. this in cost cases, supports with Finally, data of the eliminating complexity point consolidating for reducing our increases and macro and remain less management. a customers environment. MongoDB the many are to combination This wide customers the developer looking They do dramatically resonates

efficient. operational incumbent Search an media the brands technology search Atlas world. Atlas replaced a In customers Search not they true as well of homepage onto only ease partner, on example, queries MongoDB as the the them Atlas become of the in to For most but overall from now cost functionality search also powers The queries one a were because alongside partner customer consolidating single as to of running of the accelerates view the pace recognizable a platform. drawn drives innovation, sports short, other savings that with more

customers investments continue to teams We do and customer-facing both. to deepening are products, our to in enable partnerships

and teams of platform as data a a XX transactions from application about infrastructure, various validates million led base. of These a addresses customer solutions the include free Fishbowl company across their AT&T across Atlas handles trends data single to to Now on their Trend were into of technical developer operations. day, a as I'd their but world Atlas, Customers platform. key the like management power by journey. The our leveraging applications running duplicative view and turned the around Micro. customers unique disparate reviewing and industries depth and modernization database are data to to element full AT&T, selected million spend Atlas their information. The developer of XXX merge MongoDB our mission-critical Glassdoor minutes adoption data the per data customer management managing simplify there few location sources

to well capabilities streams data they location to track Now as chain rely geospatial information products quickly to and built-in easily and mission-critical identify functions market changes Atlas services. time with and Atlas' accelerate for search on native as

to achieving EY, significant up the while customers to and turning log for MongoDB examples are time of Hero innovation savings. free Delivery developers' ASAP cost

of automates the clients their of MongoDB from a XXXX deadlines. data nonrelational the are of its requests Ernst as file tool, different cloud-based solution as and previous limitations lines experienced during and and XXX time and EY. performance regulatory XX%, and to across to transaction The volumes, & internal EY and concurrent work Young data much database of bat reduced manages migrated high LLP handle scale global to without significant to GVRT, countries. peak teams One strict user returns increased periods. Atlas award and under taxes loads boost, reporting transactional volumes cost by types XX or innovation digitizes preparation winners meet is able

the a Manulife, to the to are clear Playwalks of Services, modernize became MongoDB Health largest that new relational when development, speeds one and easily drag and Group, their increased life Cigna insurance transactions bring migrates selected Evernorth on database companies to the world turning model a innovation document applications. flexible migration. in it time digital of Manulife supports Atlas Atlas division the to to products market. data seamless the asset up Manulife scales offer because caused and

Using its personalization and launched allows data connectivity apps load effectively. in synchronization. one to Using mobile broaden of areas offline improve Atlas Device the app off-line cost Atlas interactions or enhance they to low to Sync, critical successfully capabilities digital customers' Manulife uninterrupted usage when ensure

third In emerging strategy deploy. results, a as more and is summary, I'm with become AI-powered And our modernize their using efficient. for choice applications. of over customers to where flexibility are our platform allows they anywhere MongoDB run quarter MongoDB pleased customers And

at Adobe roles XXXX. it Strategy Corporate enterprise. Board and Vice of agency, to Lewnes, I'm Development business Chief Officer Marketing Directors. from share driving experienced President Adobe or Ann held a over of turn subscription-based business to creative to very leadership a joined Executive I former medium-sized excited to at whether that MongoDB's the large Ann professionals, perpetual transition Michael, Before a just instrumental in and She from a a to XXXX model they're was has Adobe's small marketing in and

similar professionals of very leadership and positions and Marketing. the Ann is held of did If a including is developers, you Intel at Sales to the company, level Prior to strategy replace during at tenure what Vice next with her of Adobe, MongoDB at creative President this it doing scale. and XX-year Ann variety

Ann We the bring will Board. perspective are the thrilled exceptional for to

here's Michael. that, With

Dev. Thanks,

results our a the quarter quarter with begin and with detailed view full year quarter, both delivered we mentioned, As operationally. I'll our financially the in then fourth and fiscal finish XXXX. for of and outlook a third performance third strong

our high First, the above I'll in Total results. end up of $XXX quarter third the year-over-year XX% start our with million, revenue guidance. and quarter was

environment mission a business to new continue and our As fit the we Dev of product see platform. demonstrating mentioned, market healthy our criticality

mix. to Shifting our product

revenue Let's start XX% compared third year to in to and the in Atlas last previous the represents total XX% XX% and compared grew fiscal quarter. with XXXX quarter the Atlas. of XX%

based of related Atlas activity As the be a we which and factors. reminder, closely macroeconomic to end-user that recognize impacted application, by primarily is consumption customer platform on can revenue consumption of our

Atlas on and with than consumption context in our Let growth in quarter. QX expectations Week-over-week me some line was in the consumption provide QX. stronger

that experienced uptick this less As had given a compared we've how less you the variability and this were what improvement year. last pronounced and QX year reminder, We that, in to based in that seen we with expecting seasonal shared consumption exactly compared out. forecast played consumption to year we've to an be quarter last overall, QX year on is

to customer of Turning we the existing quarter EA appeal strength EA to non-Atlas run was selling exceeded in base. revenue revenues. part to EA our into in deals have more success continue as multiyear up expectations incremental a of workloads the result EA our strategy. and Ongoing speaks had expected. our success we The anywhere the than

recognized of the license for upfront revenues term a includes As as the from at term license reminder, and, deals years. contract is future revenue component multiyear therefore, the start

Turning to customer growth.

the in in customer customer total ago During approximately X,XXX customer our over base sales is year up count, to quarter grew mind the XX,XXX, being period. EA customers which to workloads. had X,XXX growth customer over to driven of customer year customers incremental Of which primarily in is count XX,XXX the important to count compares period. by over at the reflects direct total is third our end Atlas to the over over year adding customers count Atlas, which total quarter, addition customers MongoDB ago customers, bringing our It the in our the we ago our that in sequentially, growth in by Atlas customers new The keep X,XXX XX,XXX are XX,XXX from compared in to over period. existing

we remain they Taking are and customer self-serve because count moved they're consistent accounts, better additions XXX users of additions account, other tier. our quarter, our or out ARR, historic the net subsidiaries healthy with our as now of representing of our approximately customers trends. net self-serve overall negligible classified free that into During

net our healthy. sales of remains additions, activity terms In direct new sales

direct accounts related sales discussed continue provider and Our to the small the sales reported direct new to some self-serve. adds mid-market last reflect additions, marketplaces direct fulfill to net of dynamics sales customer cloud leveraging to quarter movement we

with at is X,XXX another ago year least customers the above to and which AR Moving quarter from in quarter had X,XXX annualized expansion XXX%. up net $XXX,XXX We ARR. on our with MRR, ended period. with ARR rate We in the

a statement. on XX% the down of up basis, million, be year from was period. non-GAAP is which the income noted. wise a gross results quarter Gross $XXX.X our in I'll representing third Moving profit discussing unless the in XX% margin ago

primarily improved improvement margin realizing Atlas. efficiencies is in year-over-year driven we Our by are that

year quarter or from XX% million in operations income margin Our the $XX.X for the ago X% to margin operating compared a an was period. third

operating our revenue significant guidance the primary strength our results and versus strong Our in the clear leverage our economics. of The bottom reason a line for unit demonstrate results operating are in indication our model income underlying is outperformance.

income benefited of In new hires. addition, the our operating timing from

incur the from Finally, timing programs, QX QX. expenses, marketing now events expect and other internal we of benefited which to in occur --

million XX.X Net $XX.X $XX.X ago a income income to average XX.X or quarter in in million based or This outstanding. third share outstanding per weighted weighted $X.XX $X.XX net year diluted the per diluted period. share million shares on compares million the was on shares of average

After $XX.X principal and into free billion taking and lease quarter sheet the the restricted of investments capital in cash ended balance and flow. with in quarter the the cash. repayments to $X.X million million. cash third was quarter. expenditures finance flow cash equivalents, million was $XX in short-term in liabilities, approximately flow Turning cash We $X.X third Operating cash, consideration

third of to in compares fiscal million negative of $X.X This free quarter flow cash XXXX. the

now to fourth outlook quarter full to year I'd fiscal turn our the like year and XXXX. for

For $XXX quarter, fourth be of $XXX in the expect to to the million. revenue million range we

to million non-GAAP the $XX to based in $X.XX income expect $X.XX estimated weighted shares of share be of million net to per be range average on million We the operations $XX XX.X diluted income from to in non-GAAP and outstanding. range

year to a be XX.X approximately estimated to board. increasing $XXX.X shares the our fourth per XXXX, be billion for from share range that range million; in fiscal full range fiscal $X.XX across of non-GAAP of year Note to average share of and based net be non-GAAP non-GAAP provision XXXX on expect $XXX.X income net full weighted the XX%. in $X.XXX million $X.XXX income the and million includes the the to the now per income tax of in operations outstanding. $X.XX billion; to We quarter we non-GAAP to guidance the revenue outlook diluted For are

our guidance. some on provide now context I'll

QX the growth be First, expect slowdown the consumption we impacted seasonal around holidays. by Atlas to

about Second, that year-over-year had mind dollars growth more keep this we of as think sequential QX, in coming several revenue commitments, both million and not in which revenue we QX last do you in from year, Atlas of expect occur to unused quarter.

for as again Third, result our QX. so year, of strong a this non-Atlas revenue far expectations execution are our raising we

QX. seasonal However, decline QX QX due usually see is we sequentially will versus different expect our greater activity. that from revenues in a our normal non-Atlas as renewal uptick to pattern This we

because decline of of EA the sequential seen year the deals. strength QX, in this multiyear for the including is benefit reason The we've

Finally, thanks points QX to are of operating guidance, increasing performance in outlook, the we for strong to XX% fiscal in again to midpoint basis fiscal more 'XX and at compared our to revenue 'XX. margins assumption the -- improvement the XXX than our increased again of an

Our that primarily by late year pace improved investment the outperformance relatively outlook increase we driven and revenue revenue our of the fact improvement year. didn't in the is significant margin this our until as

we a the us. this is given As in achieved ahead long-term result, think market short margin desirable that greater expansion of we term the opportunity year

leverage MongoDB results We're difficult inherent are our summarize, pleased to delivered a our new in with excellent ability win To model. demonstrating in business environment. quarter and the third operating

opportunity our we continue we'll long-term the we'll to While to maximize excited responsibly and value. about remain continue invest the monitor incredibly macro ahead, to environment,

to that, open questions. With Operator? to up we'd like

[Operator Instructions].

Singh first comes from Sanjit of Our question Morgan Stanley.

look this When better Atlas the trends the I growth consumption that mentioned you than results in you on at the quarter, know Michael, Congrats were expectations. QX.

in come seasonal the below that more that in pronounced the you what past than X in were anticipating Or did terms of you've you the seasonality uplift QX? showed the in that was expected? business in seen that of In terms years, that's and

Yes.

expectations. seasonality had to seen course QX. out that over the less variability just clarify, that year our with We had So is and Atlas year. for QX for into line in the expected incorporated came called We our What last of have we forecast. seen and

assume that, what that how QX played exactly be we so muted and the would And that's more happened and out. quarter seasonality year, this

much Dev, then, question. guess I a And Understood. picture bigger

players time, years this in, around I large so you And in Oracle, about company if some XX database the founded market. of an data to to and away space application compare XX journey. the it's the like XXXX, to the move was software think like the in into that like the management from space started years to of they XX kind into the incumbent

Is that map Is sort AI. the road Mongo of in applies within view? compute dawn a in vision, that that with of new particularly an its analogy your the cycle long-term of to terms

your years the XX Thanks would when models, data Oracle for wide MongoDB our clear edge. we've variety platform use way been that for variety whether is data of Sandeep. for say a enabling multi-cloud developer What cloud, even think Yes. simply or market and question, old. And at deployment very I developers were was pushing they really a the across today it it's than use platform developer on really wide larger strategy, is cases we is our of the very we're strategy on-prem, essentially

of that's ahead we have don't itself, that us. We really think lot our and of the we strategy. see space runway need any to get a And into application so

comes question the next Barclays. of line of Lenschow Our from Raimo

ask wanted EA well. first. on I to as Congrats from me

on you doubled Another quarter to capacity. sales bit there? remember I little drivers seem do Can the more there. strong talk Because down you on of kind very a

put wanted of I think existing kind that that driver? sales accounts. junior the guys main you Is it was to on

we Can kind we where then are it would quarter because more is one lot have of second better a And than like speak modernization a what it's be up thought possible? Or the you that of picking for follow-up to have in more like Michael. kind numbers there? I row

Yes.

to whether our ability run also the they the our another that EA that to speaks I MongoDB their stay is And value customers. without one think outperformance, or rewrite on-prem having can So move model, build future-proof they customers really application for to cloud cloud and for really Raimo, the deployment cloud. with fact the on it anywhere to to where move to from essentially very strategy, do compelling regards

of existing still customers cost lot you As want infrastructure. still leverage the largest said, sunk -- their lot also have customers they and a to especially data a of

lot building they still to So have also get and cloud when that will they But the to customers a of on us on-prem for of so. remove deploy ready MongoDB, future. the the platform optionality do they're benefits foreseeable a by told modern infrastructure -- the what

Yes.

customers I on thing, oriented also, other for know, run but sales isn't the a know be audience, to as we products. be The We additional customers. we've of you business to have to And -- sales brand basis, the tends of just Raimo, EA. broader channel EA a don't said tend EA -- to existing on new before, tend the around new ton then

follow-up then Perfect. is And more around Okay. the it's AI.

Search example. I that up, if And customer around have their Vector how for for very that really is our a for a seems compelling. improve it getting you and the better, guys lot to like experience they clients demos at facing look customer seems use that straightforward Search it So

through? handle How for terms margins more computer should of the gross in do the implications revenue, then cost to coming about extra to that we have What what you Like for also be a extra Michael? to think you, able -- are lot is do it? but

Yes.

little nature think plenty workloads to a I the of it's So early tell. depending what in the application There's underlying obviously variability too the of on is.

early think direction a give it's that. little strong a to to I So

I the roughly efficiencies is made. we're very the business. I Atlas progress that driving that certainly referenced continued think in of X/X margins, with on more the broadly we've been margin happy we've

overall. is So still as that lower continues to increase, Atlas margin

make gross have of a call we're quantification front. pleased AI. that but margin next over the on early to several will so the on the years, margin some specific And impact But or I impacts really too think

just that announcements can to you to isolation. add you made Raimo, also the workload now was do of one And that, Yes.

Search your functionality, can or for So cluster. Vector you scale those nodes independently overall Search of

really that configure the customers to right of efficient is what at most level to the performance really allow So cost. have does their clusters

So different we've scale you nodes on cases, can and making on based very sensitive sure based the your up needs. different on been that use down application

that compelling a for very customers. be value will definition, proposition by So

moment, One please.

question comes line next from Our the UBS. Keirstead Karl of of

Maybe people I'll to a this I are data forward this spoke wanting lot direct line question refrain Dev, data of order to -- customers, feeling Dev. the you estates infrastructure. their to pressure on about think even get in about moving modernize on hearing AI And customers enterprises in their advance of initiatives.

do I'd yet, just feel sales start Is an like that roughly, we do this beginning you pull to if through? in teams this journey. isn't to to that conversation revenue Or where revenue are and is think lift? actual result a actually like when are deals to translate ask And having? in your that it you might

Yes.

a AI, points. is with some Karl, of right. way, of absolutely a code. lot in There a couple new make data focus you're data I'll So becomes on because it

you can your with data proprietary to more really build value smarter allows much your train You drive that models applications. and

thing into legacy that those this that updated. have And those interested being platforms. data can't you legacy it's is data Now customers right real-time leverage that why of is warehouse platforms these the applications, modernizing of with able all running and data then before. so key platforms than many ever sort always operational potentially in really constantly That's data. of now on legacy applications use process the of are batch because in much some customers, e-tailing that trapped operational now they still data most more are do to a for is And

early your Karl, We one say, of would definitely And I say the opportunities long-term largest past, risk underestimating this early of there's for the very, long-term it's term, would think the in the the this question, days. But I we is very overestimating of in that still the part long impact of the our of very be short will second a term days. a believe we're impact but impact. business. your said to definitely I've

my the metrics commits. Mike, you from pressure. Great. even a a reason under a come multiyear on were last could call for cash to DR of ask little some if of Okay. And And and kind a this had away mix follow-up subject. flow pointing I bit think your about talked Atlas to like little more I to that shift as you

is of under This Cash better. see impacting maybe describe a DR I metrics? still some flow quarter, revisit and that pressure. phenomenon it's Can was little these bit you how

Yes, things. of a couple

friction been over we've aren't for We've helpful of beginning, deferred ton -- talked or calculated billings said force. is about how the we've the trying we provide terms like some of run those don't do As from in metrics super sales of insight revenue business. or last to how a reduce the of things one also the couple years, of the

includes that commitments. reducing upfront the of Some around emphasis

that. landing deferred things through helps flow upfront that as less and or like And does and the through accelerate and statements like financial so workloads flow that, that new will things

force of And cover so it us a allows from ground more sales synthetically perspective. to sort

continuing that do go through. you to so see And

We to was quarter. growth committed Atlas last Atlas stat, revenue statistic declined XX% but year-over-year, it. XX%, The try the as just last quarter dimensionalize shared of the and one dollars help way

We the flow how year of think, deferred. roughly doesn't talked, through I about earlier Atlas XX% also in

to forward-looking of doesn't those other the might helpful kind like companies. not that used think or that, points rest explain It sort of of why will metric in people insight hope of be are I up the all of a it data And to help give seeing what you kind that's you're and maybe so line that provide.

please. moment, One

of Reback from of Brad line Our next the question comes Stifel.

point trend it bleed perspective? multiyear question DR it down? Michael, of maybe following being your from commentary. a a stabilize you is financial as stop or kind headwind this When up last a should on should what in At that

Yes.

factors. will One a I'd there the we dynamic. of key that think trends to -- but is right? a the So Obviously, you've we continues on a And Atlas overall guide to say got things. it's mix, Atlas this that that on, extent not so thing sort X be couple grow, focus provide It's I will are of not something to. headwind

And then we historic within to that there's footprint, similarly, and everything Atlas the commitments run else. this even need renewal current cycles through

out. I while a still take to will so think play And this little

Great. And customers type customers time these are which the what or gotten relates to workload reduce began to of these of to gears, some as Copilot you as switching it tools? efficient much say, feedback code they've faster them net trial getting will been then tools pace new from How have with able to using Dev, market?

Yes. using. lot between really worse, different different the who's output quality We the It a difference of on Without get better, who's depends the tools. which from different see they're definitely a commenting tool answers on we in customers. of

I think tools time mature. to to these for take going some it's

lot testing So of a I a lot you're customers think prototyping. seeing do of and

I lot would a IP also doing is shrink-wrap on applications rights because there's about licensable a to internal-facing then they're questions if of end still or copyrightable as service be this customers. also tell software and you offer this what of lots they that their and potentially

being the by the facing we're of sophistication this productivity more seeing applications vary of So do app do built. work internally and also gains the vary tool by but really on

use people trying But on for that you out there's it's the a case tool So use. and know I really and the to number. me quoting improvement. XX% XX% customer depends to hard real the there give or they're it

me for hard give be number. a would to it specific you So

of question Citi. Our Radke of Tyler the line next from comes

road a some Jim Mark this of in you what from enterprises? earlier Can terms database who of replacement, has to product of talk priorities, the hired experience map you you're quarter, larger about Scharf kind the of just to Porter's industry. sell his in lot So accelerating AWS,

Yes.

years background, So think customer who he had don't you then roles fastest-growing for which know variety last it, Jim's Identity at X the Access those database business. AWS XX And is if over AWS's spent about He's largest which, and he about business, AWS, of roles, DynamoDB to has the people he took Management nonrelational a but ran then at ultimately business AWS. use. every meaningful

scale. but to, has perform, it's perform not massive a only So that at service

built kind time. and level for technical to given appealing in lot at our scale ambitions to the in services strong has -- of of we ultimately dealt that DNA. He he's some very get was very of a of mission-critical that relationships brings industry. network business X AWS to fact obviously He the obviously us expect and to point our us The

expect we So the team the his him us grow world, relationships. to help around leveraging

mean, And what that quite slow really encourage the have, of right really impressed been he's still we now, to He's of need of to he's talent -- of assessing the the with quality we I to I state in priorities, kind do go them current business. of fast. terms is but kind go

there's base So not he take his this next like it's set the the in time broken. to really really starts us team, And prioritizing business, understanding understanding code scale terms really level. the before some helping massively to understanding things up the of what do. to It's

November, within your QX expectations. and more things month stronger? the in the And additional was variability just weaker a And follow-up color were Atlas quarter? curious, of it In start line other would any talked improved kind -- the had helpful. in, holiday consumption curious, volatility with of ahead further was there know words, there it given at did be during lot Great. Just equity for a did just throughout of I'm least, seasonality? of economy, the I any then the I'm markets and about how Michael. you

Yes.

was benefit seasonal relative in it fiscal we is variability that to be were fact smaller QX like consumption relates our had improvement, was of less fiscal as QX a The to seen Atlas QX. you little it line a more the exactly in So the given said, in out. in There to 'XX, And to it played But that the how with back results expectations. QX, than bit that's quarter. seasonal in we've 'XX. expected half

QX, given As back typically, it relates the slowdown. is half holiday weaker to the

so And people that little helps hopefully, understand bit. a

please. moment, One

Sachs. comes of the Goldman Rangan Our of next from question line Kash

holidays, the congrats results. happy Michael, on and Dev

out how fitting XXXX? going respect MongoDB So they 'XX, no macro 'XX to feel some particularly calendar team verticals get aspects impacting how to to into So going the stand you to in wanted impacting you to with conditions priorities is into about? into longer just relative or Any are business? that does are understand excited the feel customer therefore come that as how of management maybe

for thanks question. Hi, Kash, the

negativity I say -- we calendar Where last was that things there in coming but XXXX. getting more we I'd much are Fed more of was think And sense outlook from see getting cautious. year, terms probably people could worse, getting compared it the this see raising don't the with year, better. things really into don't last year rates, you

I clearly high are, So category. We the see being that any also, and ensuring for focused the that being prepared But on to costs clearly definitely would priority customers innovation we said, distinction the ROI. as nice-to-have a I must-have remain and between they being mentioned may sensitive in investments, remarks, a we say, in customers. have in first

in -- or well-positioned So there's we're industry amazing week, would say, general, last we material segments. level customers. conversations of re:Invent of an see no senior do any vertical of set use of or mean We we feel terms any real and in at lots I that cases change in kind with had geography. we I were -- across

on people really And mission-critical by platform I view platform we're that a can as think a our customers. I term. bet all us they as long think viewed

say I and to geographies. And and more would say, so point and And for use would MongoDB we I leverage trying less, focus cases. across on see that's industries like solutions about consistent like pretty more that, more

clearly, The things is stabilized. have other I'd thing Yes. only Kash, add,

I numbers. people and are not of mind. 'XX. key big 'XX be But assumption determiner And difficult We out, a clearly fiscal people's the the non-EA fiscal will keep sort of keep But should in EA the in how looking are macro big mind. terms in compare think that that guiding or probably affects to outlook there's just things the those

comes of line of question Oppenheimer. Kidron from next Ittai the Our

prepared to go numbers. back Michael, the of in one remarks. to comments your want Nice I

was the me this you the correct third in deals, think down expect be I've business quarter-over-quarter got think if how I to non-Atlas had about wrong, XQ talked in guess a unless you fourth multiple non-Atlas quarter. multiyear Because just question quarter there I your XQ would forward forward multiyears? is XQ that pull on from also Is into business? I my a pull affect why element there

It's No. impact when just of It's take up into license not the about forward. you deal, recognizing XXX account a wind a a multiyear you pull lot of upfront revenue.

you what when a basis, you that means of about so the on think delta there. difference see the And sequential

we've expectations. than even but with the the And QX. EA of our just though think the QX. we EA in continued of in QX, given shows we thing, is, our people strength only other seen outperformed part the don't year, effectively outlook, in in guide to throughout that Ittai, including full our will, the year was think raised more strength you for of product, I I was QX, line strength given in that the kind EA raise Atlas beat within And EA. if

types common here it. dollar Got use of about vendor on do potential competition can a maybe fresh in how is cases? there And to I you the on but this the for basis, of the expect a know I out here. opportunity those more Dev, is customer per Vector oven here, talk Helpful. think see then, that And of Search, kind you out there about one

Yes.

disrupted an risk are with in Vectors a a think and start X X, point recognition months of Vectors time, be that another every we architecture. platform and that ultimately made that would them? point of And it wondering, a lot database clear there really first. lot were at second form that their index there people we we there could lot into by the is incorporate believe was solutions were some and ago, say that of in me a let I question interest that got So would name databases of I Vector

Vector the I and And that it's cohesive would would argue the technology played integrated developer very be made really that the functionality of the winner part workflow. as out. really

customers, said a lots on came remarks, called spoke by recent analysis firm -- in I the prepared top done out of in a really As NPS. of Retool of there that terms we to was consultancy and

It is going we to big like feel materialize, by the days. even growth product way, And wasn't other of a big of it's business. demand for the seen this the opportunities preview a And product. to a take again, our our customers. Again, from big, GA product. is, this We've lot one opportunity. was time but It's early

would with the say, cases revenue still in it's around opportunity, hard That really that use of starting are kind early are I technology. Because because the terms event. with customers to being people still said, the are quantify playing now of,

for for basically is as an seeing, using geospatial company doing in data of the using to One terms its it I energy that get in Vectors are UKG they're is work Energy, insights we better to assistant essentially AI-powered But mentioned, getting they're people. is terabytes terms of of using images provide from and the oil. drilling European

So it's early still very, very days.

variety vary you give of on exact depending non-AI like the in of our data. workload the even numbers. to customer, an a workloads, hard the lot amount users, So number Even the can today, general

to similar going So it's business, depends I really our the use on be to think case. core that which is just

of America. comes the from of Bank next of Brad Sills question Our line

for like going XXX,XXX. trajectory or count the than a Is result Wanted quarter. to in of this they there In any there things? point they that on be And question ask customer a those bigger? greater get customers around starting what landing other It path looks terms that level? getting words, just change the the nice real X they are to faster? bigger? to driving to are Are Or would

viewing glad the customers added in They're speaks to that history. think platform. think, add, which to XXX,XXX mission-critical really on I is MongoDB. largest What customers a company's I I'm it Yes, out, called Yes, that is Brad. we're we run XXX more as the are workloads you going -- MongoDB increasingly -- and think this quarter, more I

of on one revenue. it's workload definition, its kind that by rare drive So will that own

a that, and cases. that's as as just recognize of part use support us think workloads I They few consolidating set people we a driving And we are earlier, indication, offer onto for vendors. said broad of see that what's where that really we're the stack And a obviously of really multiple is results the that. standard viewing So happy infrastructure number. to their

We developers using a MongoDB. that mission-critical are love and really general-purpose, truly their platform

Wonderful to hear. may, if more, And then please. I one

platform. that to that, trying I'm who you and streaming some On for do sense viewing Relational cycles workloads you Relational? around receptivity run customers Atlas and case just search that on those of how get within solution, those capability? a is like are With besides want Search, also the that for commentary ramp to customers one these finding as newer Migrator for the streaming, single Mongo platform that -- might

Yes.

search instances, because and built a yes, database. our actually, the our one to got customers. to of search were actually some we data lot homing customers of MongoDB reasons dual many we sort from is So In of feedback

API. much also databases, X not that only in manage in -- offering much you're the but keep they not because platforms. we consequently, connected with rather had manage data sync, X don't to customers like So one solution a one understand those would told all us why have it's plumbing that it database we platform And

functionality, more popular. search ultimately more which really desire becoming out that to our drove And and build our is

you of the set of more I can really the terms So cost-effective data with -- in the a address of customers. leverage nimble of cases, it simplifies the be broad architecture, customers you they And semantics friction have for And the how think use can one platform, more in data you kind really point if what's to is terms resonating that's architecture. of the set simplify platform, can can that the use more you be. remove and

comes next Our the from Jaluria RBC. Rishi question of line of

I look into color, you can give what Maybe you bit by days. you seeing maybe diving know bit for. But start line definitely where quick that it's of then follow of What And to I've kind give got a be early little tool Dev, utilizing it, like? does really said little Migrator. a these us a the are of are early helpful. adoption sort I time usage color there that want customers in are can Relational of Any of you terms up. workloads would

Yes.

repository platform of have So of imagine, around these years, legacy map schema And legacy been does the a require essentially off requires you XX apps. a things. XX It of X for -- migrating lot work. to the the a a between large legacy have lot to again, can to platforms onto people the of as have given platform. you new platform another platform old One,

application then time. move have to you and then And things to the those data have some X rewrite code. took the You

So business took we net time public, we went public feedback. When at the Migration. was of you heard XX% might company new our remember the Relational that actually

to bit tax So pain customers and on such a in they basically more were be switching were costs. heavy lifting of wanted to that move undertaking a the modern pain a But because platform. clearly, can

automating schema so on mapping from And to start the movement. feedback essentially, we build and customers the data tooling based

relational services monolithic it they're much the essentially, start ROI now associated just actually of Gen thinking about a one -- rather down also ROI, micro some availability a quicker more lock also an application. and with different first, app can you automating efficient can step, into the off Now what break making. the of be than of the more moving AI, start so services parts rebuilding rebuilding And we investments app in can the cogeneration with in and cleaving or

for big early in want very a But get. be big, to opportunity very days. view to a we opportunity. again, us there's as So the here I growth still We're clear, long-term this

on us pilots. got interested You've in really with doing some interesting some customers, things who are working

are to early Migrator really Gen Our engineering focused next automating of very, and on days product the level, this, in and the leveraging Relational we're very AI. field really but teams

about to is least of All about helpful. something a MongoDB for talking And really been at kind right. -- has then Wonderful. had wanted you've this while. know ask I serverless. I That's

Given embrace tailwind a could be and to our having rationalization feels customers because like especially optimization serverless, how and out for cloud natural to lot of and overpaying it were footprint, the that concerns it. you to around optimize MongoDB figure a early

kind in serverless that years adoption a talk be consumption how opportunity? this traditional about like adoption in in what maybe next the over seeing terms of could bit versus you're you little Atlas. adoption And several there, of just what about look thinking we should Can terms of

Yes.

when talk don't about clear, case we and that customers So to can what start is planning, they down be and workload that compute other to up what needs the use on basically, whatever serverless, the have think scale resource are. about thinking scale is the the and capacity of needs based just about

there's interest lot been customers. of so from And a

At workloads, first But of days will high. functionality. provision to become that service to the our the will a the time, wanted receptivity way go think and stage, term functionality that provisioned. be dedicated are ephemeral they every has most long over and want leverage We able it we're They was didn't in a applications serverless almost the where of to use cluster. femoral lot our been workload serverless. Because very be early

can those about solutions, for that they team offer capacity They more -- planning. usage that architecture our similar MongoDB -- And becomes and app, platforms worry up down. the you're attractive development build up and goes because their just can the and know down legacy scale as in right, much can't and background a team they to as doesn't the infrastructure it's have usage

Piper Our comes Brent Bracelin next of the Sandler. from question of line

on Brent. Hannah This is for

at we continued point, remain structural the Subscription shift but remained the mix XX%-plus to of you with Just Michael, straight me. that margins that are one gross know a even next the year? where above into XX% Atlas, improvement I quarter, efficiency Atlas. gross second can range mentioned margins at scale for for to

Yes.

you not XX% very we're subscription So Enterprise it, And Atlas margins. Atlas what X/X". on gross about "only is I margin basis Advanced I -- if while in pleased performance would a lower think QX. to be with gross think continue I than say margins do the think margin is

a between And the delta two. is there still so

of And so have I increases as think Atlas will revenue. percent that, slightly as a overall origins that effect dilutive a

from of line Our question Patrick Scotiabank. Colville comes of the next

Vandrick This is Joe Colville. on for Patrick

As sales the about it spending XX% platform. $XXX,XXX customers direct are on over like of of looks XQ,

longer over accounts. percentage the opportunity sales how can curious Just the trend existing term. where customer within you think big And that these of direct is kind

wallet share in small still a believe have Yes, Joe. we we accounts. very of I would most percentage say that that

percent smaller in direct customers, share quite wallet the sales the small. share, obviously, wallet bigger so of most is our customer, And the still but

we there. So a see big opportunity

And our focus go-to-market our business is a runway as we continue. big terms part came with customers. workloads business, quite for new talked long that for big a from about to And trend in of new the our acquiring new of teams. is And existing that

for used touched who feedback And but Search Vector I you customers, in have what's this, Great. data. obviously, quite those from Search on then kind more me. bit preview? Vector a one of the just mean more been comes with And

don't a So receive unhappy? surprise and sure how making customers you are end up that bill

Yes.

we has came Obviously, were high, with score. the on product in But Search of We been public this preview, highest the a feedback when even And mentioned in Vector using of report available marketplace, we lot are who earlier, as feedback. the don't it our So getting people, was very that to out. the alternatives. customers. to we talk had to NPS our pleased own that our own preview we're talk just see products all out folks, then

why customers integrated then Because you So one unpack if tightly MongoDB? do like using that, it's solution.

together. to very, case. becomes much You data, It either data and particular been solutions some or Metadata then ] point the can capturing use cloggy data And attractive. integrate use Vector just regarding [ versus and more that put using very tightly becomes seamless solution that's easier

think use a than, approach. to better that's reason alternative big why about we workflow much developer's and any the friction the say, us MongoDB I from so remove how makes other approach So

amount those data will of And your Vectors amount generate amount builds, of drive memory-intensive. of terms data In of the can be question the the obviously and around the on nodes. obviously, usage Vectors you

also increase search scale your so your particular of introduced without search especially the having of we nodes your of application, you one That's reasons overall nodes to cluster. the can dedicated asymmetrically nodes size

underlying for big to your usage, So you're nonusage. the point, not, for soft for bill

obviously, So that are that you becomes a cost-effective memory this. way differentiator the more that's people incremental -- that for and only really that nodes And much need for And to MongoDB. nodes another do versus compute scale don't.

call that closing is we Thank conference. to today's today Ittycheria, you. all over have like for I'd to for the turn Dev remarks. CEO, any That time the back

business everyone anywhere I appreciate had proposition call want data you. reiterate just the Thank strategy. validating the today. quarter of strong I run performance, new we that our platform and joining of another to developer value our

building drive a our on Vector especially customers we Atlas while which powerful accelerating Search, momentum strong their emerging seeing are applications. pace as help solution AI AI innovation. We to best-in-class greater for of And efficiency strategy, is continue also

and that, we'll I talk to your soon. with time, So appreciate care. Take you

this Thank conclude does you. you for Thank Ladies and conference. today's all gentlemen, participating.

disconnect. You now may