Significant developments have occurred since Dev Ittycheria assumed leadership at MongoDB, the $26 billion database company where he has been serving as president and CEO since September 2014. Under Ittycheria’s guidance, MongoDB has transitioned to the cloud, navigated through an IPO, shifted focus from open source, introduced a venture capital arm, and expanded its customer base from a few hundred to nearly 50,000.
“When I joined the company, it wasn’t clear if people would trust us to be a truly mission-critical technology,” Ittycheria shared with TechCrunch. “When I joined, it was doing roughly $30 million in revenue; now we’re doing close to $2 billion.”
Despite the successes, MongoDB faced a security breach five months ago, momentarily jeopardizing its reputation in the industry. However, the company managed to contain the breach, underscoring the importance of maintaining a strong reputation.
Amidst the AI revolution sweeping industries, TechCrunch sat down with Ittycheria at MongoDB’s new London office in Blackfriars, which opened the previous year.
MongoDB’s London office. Image Credits: Paul Sawers / TechCrunch
Vector’s Embrace
Over the years, databases have evolved significantly from the era of IBM and Oracle’s relational databases. The demand for flexible, scalable, and cost-effective data storage and processing, driven by the internet’s growth, has enabled companies like MongoDB to thrive.
Established in 2007 by veterans from DoubleClick, MongoDB initially known as 10Gen, has emerged as a prominent NoSQL database, aiding companies in managing large data volumes.
Before his tenure at MongoDB, Ittycheria founded and exited BladeLogic, a server automation company, for $900 million in 2008. He then served in various board and investor roles before joining MongoDB a decade ago. Ittycheria succeeded Max Schireson as CEO who stepped down after 18 months due to family reasons.
Utilizing a document-oriented model, MongoDB has flourished with the surge in mobile and web applications requiring dynamic data structures. The current AI wave is driving a transition towards vector databases, well-suited for large language models and generative AI.
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