MongoDB smashed analyst expectations in Q3 earnings reported late Monday. Its revenues hit $529.4 million, up 22% year-on-year.
Its multi-cloud “Atlas” data platform (managed MongoDB database and range of optional add-ons) were 68% of total revenues and up 26%.
Notably, on-premise deployment wins also surged: "Our non-Atlas business significantly exceeded expectations in part because we benefited from a few large multi-year deals as customers continue to value our run anywhere strategy" said CEO Dev Ittycheria on an earnings call
"We continue to invest in our legacy app modernization and AI offerings as our document model and distributed architecture are exceptionally well suited for customers looking to build highly-performant, modern applications.”
MongoDB said it expects sales of $517 million at the midpoint of its range for the current quarter. Analysts were projecting $509 million.
The MongoDB document model is easy and fast, say company leaders. Unlike SQL databases, for which you need to determine and declare a table's schema before inserting data, MongoDB does not require documents to have the same schema; i.e The documents in a single “collection” – the equivalent of an RDBMS table – do not need to have the same set of fields, and the data type for a field can differ.
“An object in code can be stored directly in the database without complex transformations, and can be retrieved as that same object when needed… dynamic structure enables quick evolution of data models while enforcing schema controls to preserve fields, values, and data types consistently across documents” as product SVP Andrew Davidson earlier explained.
That means for developers looking to build applications that evolve as the world does, they don’t need to go in and overhaul their SQL data schema.
(Relational databases, in which you pre-define your database schema based on your business’s requirements and set up rules to govern the relationships between fields in your tables, require a procedure that can take the database offline or significantly reduce performance if changing data schema – e.g. when, adding new capabilities to an application.)
Whilst MongoDB has a footprint in the vast majority of Fortune 500 companies, it sees the opportunity for expansion as significant.
Ittycheria said: "We're investing time and resources to educate developers in large enterprise accounts and uplevel their MongoDB skills.
"These organizations have thousands of developers and as we penetrate them more deeply, we encounter developers who have historically only built SQL applications and simply do not know how to use MongoDB to its full potential," he explained on the late Monday earnings call.
"In our experience, educating these developers on the benefits of MongoDB drives significant incremental adoption of our platform."
The company is also increasing its professional services delivery capabilities, both directly and through partners, its CEO said.
He added: "We are optimistic about the opportunity to accelerate legacy app modernization using AI and are investing more in this area.
"As you recall, we ran a few successful pilots earlier this year, demonstrating that AI tooling combined with professional services and our relational migrator product can significantly reduce the time, cost, and risk of migrating legacy applications onto MongoDB. While it's early days, we have observed a more than 50% reduction in the cost to modernize."
Among the companies working on a major migration is one of the world's largest banks, which is exploring taking its Sybase applications to Atlas (see our partner video with MongoDB and Accenture above.)
The company trimmed net losses from $29.3 million to $9.8 million.
