{"id":4744,"date":"2026-05-29T21:13:16","date_gmt":"2026-05-29T21:13:16","guid":{"rendered":"https:\/\/www.fintechpulse8.com\/?p=4744"},"modified":"2026-05-29T21:13:16","modified_gmt":"2026-05-29T21:13:16","slug":"morgan-stanley-resets-mongodb-stock-price-target-after-earnings","status":"publish","type":"post","link":"https:\/\/www.fintechpulse8.com\/?p=4744","title":{"rendered":"Morgan Stanley resets MongoDB stock price target after earnings\u00a0"},"content":{"rendered":"
<\/p>\n
There is a specific kind of earnings report that is genuinely hard to read. The one that beats on revenue, raises full-year guidance, shows improving margins, but still leaves investors asking whether the most important growth driver has actually arrived yet.<\/p>\n
MongoDB (MDB) just delivered exactly that quarter. And Morgan Stanley’s response captures the tension precisely.<\/p>\n
Morgan Stanley raised its price target on MongoDB (MDB) after the company\u2019s first-quarter fiscal 2027 results on May 28. The note’s title said it plainly:\u00a0<\/p>\n
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“Entry to the AI Winner Circle Still Pending, but It’s Just a Matter of Time”<\/p>\n<\/blockquote>\n
MDB is down 24.65% year-to-date compared to the S&P 500’s 10.78% gain, according to Yahoo Finance. <\/p>\n
The stock is being priced for a company whose AI moment has not yet arrived. Morgan Stanley argues that the timeline is getting shorter and that the underlying business is strong enough to own while waiting.<\/p>\n
Morgan Stanley raised the MongoDB stock price target to $380 from $335<\/h2>\n
Morgan Stanley raised its price target on MongoDB (MDB) to $380 from $335 in a note shared with me at TheStreet, maintaining its Overweight rating. This came after its Q1 fiscal 2027 results actually showed solid results.<\/p>\n
The first-quarter scorecard from MongoDB’s May 28 earnings release:<\/p>\n
\n
Total revenue of $687.6 million, up 25% year over year, beating consensus by $23 million<\/li>\n
Atlas cloud revenue up more than 29% year over year<\/li>\n
Enterprise Advanced revenue up more than 13% year over year<\/li>\n
Full-year fiscal 2027 guidance raised \u2014 FY27 revenue midpoint growth lifted to approximately 19.5% from 17% previouQ2 guidance calling for 24% growth, approximately $31 million ahead of consensus \nSource: Morgan Stanley Note and MongoDB First Quarter Fiscal 2027 Results\n<\/li>\n<\/ul>\n
The guidance raise is the headline number Morgan Stanley wants you and other investors to focus on. The full-year outlook was raised by $60 million. In fact, that is more than the Q1 beat and Q2 raise combined, according to the note.<\/p>\n
That means management is seeing something in the second half of fiscal 2027 that justified raising beyond what the near-term results alone warranted.<\/p>\n
Related: Bank of America resets MongoDB stock price target ahead of earnings<\/strong><\/p>\n
This here is the one soft note from the note. Atlas\u2019 29% growth came in slightly below elevated investor expectations of 30%-31%, particularly after strong recent results from peers Datadog and Snowflake.\u00a0<\/p>\n
Management described Atlas as having become more predictable and less sensitive to individual customer movements, characterizing the current trajectory as sustained growth rather than an imminent acceleration.<\/p>\n
“We delivered better-than-expected first quarter results, as our go-to-market teams continue to execute well,” said CEO CJ Desai in the earnings release.<\/p>\n\n
At MongoDB Local London, MongoDB announced seven new platform capabilities specifically designed to close the gap between AI experimentation and high-performance production deployment.<\/p>\n
LightRocket via Getty Images<\/p>\n<\/figcaption><\/figure>\n
Why Morgan Stanley raised its MongoDB target to $380<\/h2>\n
The $380 price target reflects a 37x multiple on Morgan Stanley’s calendar year 2029 Base Case free cash flow estimate of approximately $1.27 billion, discounted back to calendar year 2027 at a 10.3% weighted average cost of capital, according to the note shared with me at TheStreet.<\/p>\n
The multiple expansion from approximately 33x to 37x reflects the firm’s view that the AI monetization timeline is compressing. Morgan Stanley’s core argument is structural: for MongoDB to see the same AI-fueled inflection that Datadog and Snowflake are experiencing, AI applications must reach a specific maturity threshold.\u00a0<\/p>\n
Related: MongoDB just got a reality check from Wall Street<\/strong><\/p>\n
Such thresholds include mission-critical to the end customer, significant product-market fit, and material scale relative to the millions of existing applications already running on MongoDB.<\/p>\n
That process takes time. But CEO CJ Desai’s commentary on the Q1 call was notably more constructive than in prior quarters.\u00a0<\/p>\n
He described early AI deployments with enterprise customers and burgeoning momentum with AI-native companies \u2014 with MongoDB being deployed for mission-critical use cases and expanding within those customers over time.<\/p>\n
My read of that shift in tone is that Morgan Stanley is right to mark it. When a CEO who has been consistently cautious about AI timing language starts sounding more confident, it tends to precede guidance revisions that move stocks.<\/p>\n
The product and partnership moves that are building the AI foundation<\/h2>\n
MongoDB is not waiting passively for the AI tailwind to arrive. The Q1 business highlights show a company actively building the technical and commercial infrastructure to capture it.<\/p>\n
The LangChain strategic partnership, announced in the quarter, transforms MongoDB Atlas into a unified backend for production-ready AI agents \u2014 integrating vector search, persistent memory, and natural-language querying into a single enterprise-grade platform. That is a direct answer to the enterprise AI deployment use case.<\/p>\n
At MongoDB Local London, MongoDB announced seven new platform capabilities specifically designed to close the gap between AI experimentation and high-performance production deployment, according to the earnings release.\u00a0<\/p>\n
More Tech Stocks:<\/strong><\/p>\n
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Nvidia\u2019s China chip problem isn\u2019t what most investors think<\/strong><\/li>\n
Quantum Computing makes $110 million move nobody saw coming<\/strong><\/li>\n<\/ul>\n
The acquisition of Clarity Business Solutions strengthens MongoDB’s U.S. Federal vertical. That\u2019s a customer segment with both mission-critical requirements and significant AI investment budgets.<\/p>\n
New leadership across product and sales \u2014 including a new Chief Revenue Officer, Chief Product Officer for AI and Emerging Products, and a formalized Chief Information Security Officer \u2014 positions the company to execute faster on the opportunity CJ Desai described.<\/p>\n
For investors, the MongoDB picture is a company where the core business is growing consistently, margins are expanding, the AI opportunity is visible, and management is increasingly concrete about it.<\/p>\n
But the stock is priced for a company whose best AI chapter is still being written. Morgan Stanley thinks that chapter starts arriving toward the end of fiscal 2027. At $380, its price target suggests the wait is worth taking.<\/p>\n
Related: Morgan Stanley resets Walmart forecast on high inflation<\/strong><\/p>\n
There is a specific kind of earnings report that is genuinely hard to read. The one that beats on revenue, raises full-year guidance, shows improving margins, but still leaves investors… <\/p>\n","protected":false},"author":1,"featured_media":4745,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[246],"tags":[457,5362,479,100,481,480,91,1196],"class_list":["post-4744","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-popular","tag-earnings","tag-mongodb","tag-morgan","tag-price","tag-resets","tag-stanley","tag-stock","tag-target"],"_links":{"self":[{"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/posts\/4744","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4744"}],"version-history":[{"count":0,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/posts\/4744\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=\/wp\/v2\/media\/4745"}],"wp:attachment":[{"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4744"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4744"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.fintechpulse8.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4744"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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