Product Thinking Podcast: Episode 209

From Databases to Developer Platforms: The MongoDB Story with Andrew Davidson

Date: February 5, 2025
Host: Melissa Perri
Guest: Andrew Davidson, SVP of Product, MongoDB

Episode Overview

This episode explores the journey of MongoDB from a niche open-source database to a leading developer data platform. Host Melissa Perri and guest Andrew Davidson, SVP of Product at MongoDB, discuss the evolution of databases, the business and technical decisions driving MongoDB's growth, and the crucial role of product management in building and scaling technical platforms. The conversation dives into developer experience, how data architecture influences product innovation, and what every product manager should understand about databases.

Key Discussion Points and Insights

1. Why MongoDB? The Shift from Relational Databases

Timestamp: 09:30 - 13:08

• Relational databases were king due to storage costs in the 1970s.
• As storage became cheaper, the software bottleneck shifted from storage constraints to developer productivity and scalability.
• MongoDB's founders saw the rigidity and scalability limitations of relational databases, especially during the Web 2.0 and mobile booms.
• Andrew Davidson:

  "The key cost bottleneck in computing shifted... to developers' minds. The builders had this incredible new set of building blocks, but they were still trying to build with these relational databases and those for developers were extremely rigid." (09:53)

• MongoDB introduced a document model that aligned with how developers think, enabling flexibility and velocity, and democratized distributed systems leveraging cloud.

2. Business Value and Longevity

Timestamp: 13:08 - 16:00

• MongoDB empowers small "two pizza" engineering teams to iterate features quickly.
• Schema-free design allows faster evolution of software, better supports personalization, and adapts to changing customer needs.
• Andrew Davidson:

  "You can evolve the actual data models themselves with the flexibility of the document model. Meaning I change my software based on the needs of my end customers rapidly, all the time." (13:35)

• The company’s focus on a harmonious developer experience and strategic SaaS (MongoDB Atlas) adoption fueled long-term growth, unlike other fleeting developer tools.

3. Developer Experience as a Product Principle

Timestamp: 18:01 - 21:14

• Developer experience (DX) is a central tenet: MongoDB intentionally designed tools suited to developer mental models.
• Strategic shift from “just a database” to a developer data platform that collapses multiple data functions (search, geospatial, time series, vector search) into one product.
• Andrew Davidson:

  "We've long used the analogy of being like the Apple of databases... The iPhone had just collapsed so many things into it... We want to collapse concepts that a developer will need... into the database." (21:14)

4. Product Management with Platform and Technical Products

Timestamp: 23:48 - 31:02

• Good UX is as crucial in developer and platform tools as in user-facing products.
• Developers are power-users: they appreciate great experience, and poor tools make them “roll their own,” leading to tech debt and fragmentation.
• Product managers for platforms must consider both internal and external developer experience, scalability, and commercial viability.
• Melissa Perri:

  "If we don't think about the experience of the developers internally using those platforms... we end up in a mess." (30:28)

5. The Value-Add of Product Management in Technical Organizations

Timestamp: 32:21 - 36:05

• Product management is essential in bridging customer needs and engineering excellence, especially as teams become more specialized.
• PMs must balance inbound (roadmap, tradeoffs with engineering) and outbound (customer discovery, validation) activities.
• Andrew Davidson:

  "Product managers should absolutely be 50/50 on that: inbound, outbound. The second you find yourself doing all inbound or all outbound, you lose the credibility for the opposite." (35:11)

6. Proactive Customer Engagement and Community

Timestamp: 36:05 - 39:44

• Despite company scale, PMs must continuously reach out to new and existing customers for feedback – can't rely only on internal intuition or customer-facing workers' reports.
• Certain passionate users become core community members, driving feedback and product evolution.
• Andrew Davidson:

  "My philosophy is, like salespeople are always doing pipeline generation, I think it is crucial for product people to be constantly finding new opportunities to just reach out to the customers directly." (36:56)

7. MongoDB Atlas & The SaaS Evolution

Timestamp: 39:44 - 44:40

• Early cloud usage often involved “lift and shift”— replicating on-prem models in the cloud.
• MongoDB Atlas abstracted complexity, reduced operational risk, and became the cornerstone product; now over 70% of company revenue.
• Lowering the expertise barrier and security concerns were key to SaaS adoption.
• Andrew Davidson:

  "Instead of a bunch of complex virtual machines with operating systems... you just said, give me a database and an endpoint to connect to. And the service provider, like MongoDB, would do all that backend complexity." (40:40)

8. How Databases Affect Product Delivery and Innovation

Timestamp: 47:22 - 53:13

• Most product managers don’t realize the product’s velocity is closely tied to data model and database flexibility.
• Adding features or changing UX often requires fundamental database changes and choosing rigid technologies creates future blockers.
• Andrew Davidson:

  "The hardest part of software is the state, is the data. You can change the business logic very quickly, but the data is what you're kind of stuck with forever." (48:35)

• Modern platform products benefit from document-model databases which handle multiple data needs under one roof, reducing tech debt and speeding iteration.

9. Practical Advice for Product Managers

Timestamp: 53:13 - 57:26

• PMs should learn the basics of querying databases for customer insights.
• Understanding data modeling helps bridge requirements and engineering capability.
• Melissa Perri:

  "Everybody asks me, should I learn coding? I'm like, no, you don't really need to learn coding, but I would suggest learning how to query a database." (56:57)

• MongoDB offers accessible online courses – recommended for PMs aiming to collaborate deeply with technical teams.

Notable Quotes & Memorable Moments

• “The key cost bottleneck in computing shifted... to developers' minds.” — Andrew Davidson (09:53)
• “To me, the second you find yourself doing all inbound or all outbound, you lose the credibility for the opposite.” — Andrew Davidson (35:11)
• "If we don't think about the experience of the developers... we end up in a mess." — Melissa Perri (30:28)
• "You can change the business logic very quickly, but the data is what you're kind of stuck with forever." — Andrew Davidson (48:35)
• "MongoDB kind of gave the right balance. The Rubik's Cube, where sometimes you're adjusting and want to find the perfect balance." — Andrew Davidson, citing a customer analogy (52:32)
• "If you're not writing some code... it's hard to connect with the developers that you work with every day." — Andrew Davidson (56:07)

Important Timestamps

• Early MongoDB story & business impact: 09:30 – 16:00
• Product management on technical teams: 23:48 – 36:05
• Customer engagement strategies: 36:05 – 39:44
• Atlas and SaaS database evolution: 39:44 – 44:40
• Technical decisions and product outcomes: 47:22 – 53:13
• Advice for product managers: 53:13 – 57:26

Learn More

• MongoDB Atlas: mongodb.com/atlas
• Online trainings: MongoDB University
• Andrew Davidson: Reach out via LinkedIn

This episode is an essential listen for product managers working with technical products, internal platforms, or anyone seeking to understand how data architecture informs product velocity, developer happiness, and long-term product success.