MongoDB, Inc.

MongoDB, Inc. Earnings Recaps

MDB Information Technology 2 recaps
Next earnings: December 7, 2026 (estimated) · full calendar
Q2 2027 Sep 3, 2026

MongoDB’s shares dropped 17.2% following a cautious outlook and signs of deceleration in the pace of Atlas consumption growth, which overshadowed an otherwise solid revenue increase and customer additions.

Key takeaways
  • Total revenue grew 30% year-over-year to $772 million, driven by Atlas (29% growth) and EA plus other (36% growth).
  • Non-GAAP operating margin stood at 24%, supported by revenue growth but potentially facing future pressure.
  • Added a record 2,900 net new customers, bringing the total to 70,600, with notable growth in AI-native companies and new product adoption like Atlas Vector Search and Voyage Embeddings.
  • Management emphasized early momentum in AI workloads but did not provide clear visibility or confidence on the trajectory of Atlas consumption growth, contributing to investor wariness.
  • Despite highlighting strategic partnerships and product integration within the AI ecosystem, the cautious outlook on growth metrics and profitability outlook resulted in a significant negative market reaction.
Q4 2026 Mar 3, 2026

MongoDB delivered a robust fourth quarter for fiscal year 2026, achieving a 27% year-over-year revenue increase to $695 million, driven by strong demand for its Atlas platform and strategic customer expansions.

Key takeaways
  • Atlas revenue grew 29% year-over-year, exceeding a $2 billion run rate and generating $114 million in net new revenue for the quarter.
  • Total customer count reached over 65,200, marking a 60% increase year-over-year with 2,700 new additions in Q4.
  • The non-GAAP operating margin hit 23%, exceeding guidance and demonstrating effective cost management alongside revenue growth.
  • Significant contract wins included a $90 million deal with a large tech firm and over $100 million with a financial institution, the largest in the company’s history.
  • AI capabilities are gaining traction, with the number of customers leveraging vector search and embedding models doubling year-over-year.