{"id":7495,"date":"2026-05-29T21:23:53","date_gmt":"2026-05-29T21:23:53","guid":{"rendered":"https:\/\/stock999.top\/?p=7495"},"modified":"2026-05-29T21:23:53","modified_gmt":"2026-05-29T21:23:53","slug":"morgan-stanley-resets-mongodb-stock-price-target-after-earnings","status":"publish","type":"post","link":"https:\/\/stock999.top\/?p=7495","title":{"rendered":"Morgan Stanley resets MongoDB stock price target after earnings\u00a0"},"content":{"rendered":"<p><\/p>\n<p>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<p>MongoDB (MDB) just delivered exactly that quarter. And Morgan Stanley&#8217;s response captures the tension precisely.<\/p>\n<p>Morgan Stanley raised its price target on MongoDB (MDB) after the company\u2019s first-quarter fiscal 2027 results on May 28. The note&#8217;s title said it plainly:\u00a0<\/p>\n<p>&#8220;Entry to the AI Winner Circle Still Pending, but It&#8217;s Just a Matter of Time&#8221;<\/p>\n<p>MDB is down 24.65% year-to-date compared to the S&amp;P 500&#8217;s 10.78% gain, according to Yahoo Finance. <\/p>\n<p>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<p>Morgan Stanley raised the MongoDB stock price target to $380 from $335<\/p>\n<p>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<p>The first-quarter scorecard from MongoDB&#8217;s May 28 earnings release:<\/p>\n<p>Total revenue of $687.6 million, up 25% year over year, beating consensus by $23 millionAtlas cloud revenue up more than 29% year over yearEnterprise Advanced revenue up more than 13% year over yearFull-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<br \/>\nSource: Morgan Stanley Note and MongoDB First Quarter Fiscal 2027 Results<\/p>\n<p>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<p>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<p align=\"center\">Related: Bank of America resets MongoDB stock price target ahead of earnings<\/p>\n<p>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<p>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<p>&#8220;We delivered better-than-expected first quarter results, as our go-to-market teams continue to execute well,&#8221; said CEO CJ Desai in the earnings release.<\/p>\n<p>                        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<p>LightRocket via Getty Images<\/p>\n<p>                    Why Morgan Stanley raised its MongoDB target to $380<\/p>\n<p>The $380 price target reflects a 37x multiple on Morgan Stanley&#8217;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<p>The multiple expansion from approximately 33x to 37x reflects the firm&#8217;s view that the AI monetization timeline is compressing. Morgan Stanley&#8217;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<p align=\"center\">Related: MongoDB just got a reality check from Wall Street<\/p>\n<p>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<p>That process takes time. But CEO CJ Desai&#8217;s commentary on the Q1 call was notably more constructive than in prior quarters.\u00a0<\/p>\n<p>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<p>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<p>The product and partnership moves that are building the AI foundation<\/p>\n<p>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<p>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<p>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<p>More Tech Stocks:<\/p>\n<p>Morgan Stanley sets jaw-dropping Micron price target after eventNvidia\u2019s China chip problem isn\u2019t what most investors thinkQuantum Computing makes $110 million move nobody saw coming<\/p>\n<p>The acquisition of Clarity Business Solutions strengthens MongoDB&#8217;s U.S. Federal vertical. That\u2019s a customer segment with both mission-critical requirements and significant AI investment budgets.<\/p>\n<p>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<p>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<p>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<p align=\"center\">Related: Morgan Stanley resets Walmart forecast on high inflation<\/p>\n<p>#Morgan #Stanley #resets #MongoDB #stock #price #target #earnings<\/p>\n","protected":false},"excerpt":{"rendered":"<p>There is a specific kind of earnings report that is genuinely hard to read. The&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[259],"tags":[1308,13431,394,100,1307,395,91,336],"_links":{"self":[{"href":"https:\/\/stock999.top\/index.php?rest_route=\/wp\/v2\/posts\/7495"}],"collection":[{"href":"https:\/\/stock999.top\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/stock999.top\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/stock999.top\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/stock999.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7495"}],"version-history":[{"count":0,"href":"https:\/\/stock999.top\/index.php?rest_route=\/wp\/v2\/posts\/7495\/revisions"}],"wp:attachment":[{"href":"https:\/\/stock999.top\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7495"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/stock999.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7495"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/stock999.top\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7495"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}