Developer Data Platforms

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Nov 23, 2022

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ANECDOTE

MongoDB's Shift From Software To Managed Atlas

MongoDB moved from self-managed software to Atlas, a fully managed service, as customers demanded faster infrastructure delivery.
Atlas lets developers manage data infrastructure at the speed they think, pairing the document model with cloud operations.

INSIGHT

Developers Spend Most Time Wrestling With State

Developers spend most of their time wrestling with state, so the data model directly impacts developer productivity.
MongoDB's document model maps data to how developers think, reducing impedance between code and storage for faster feature delivery.

INSIGHT

Relational Model Reflects Old Storage Bottlenecks

The relational model was designed when storage was the bottleneck; today the bottleneck is developers' minds.
Modern databases should let developers model data in objects they think in, not force code to fit storage-era constraints.

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Andrew Davidson (SVP Products, @MongoDB) talks about MongoDB's evolution from a software company to a cloud services company (MongoDB Atlas), how developers traditionally interacted with databases, and the need for Developer Data Platforms going forward.

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Press Release: MongoDB Unveils Vision for a Developer Data Platform at MongoDB World 2022
Forbes: MongoDB Extends Developer Data Platform For Modern Applications
TechCrunch: MongoDB puts a spotlight on its developer data platform

Topic 1 - Welcome to the show. Let’s talk about your background, and what you focus on at MongoDB.

Topic 2 - Data is a weird beast. It’s cheap to create, it’s expensive to move, and it’s complicated to use because there’s so many ways to interact with it depending on the use-case. So for someone that thinks about data a lot, how do you frame up the challenges of how applications interact with data?

Topic 3 - People tend to think about MongoDB as a database company, and then a Cloud database company. What did the company learn as it moved to the cloud, as a lot of barriers for developers got knocked down in that transition?

Topic 4 - As a developer today, do I still need to think about the relationship between the underlying data and the database access model needed to make that useful to an application, or are any of those lines blurring or going away?

Topic 5 - Databases have traditionally followed the CAP theorem, and different choices have different strengths and tradeoffs. As you start to think about this concept of developer data platform, how do you try and reframe those tradeoffs? Do any of them go away?

Topic 6 - What are some examples of how companies and their developers are able to think differently about how their new applications can be built with this new platform approach to data?

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