GraphQL has exploded in popularity since its public launch in 2015, and PostgreSQL is still going strong after almost 30 years of development, gaining market share and impressive features at an ever increasing rate.

These tools can pair beautifully, in particular because they're both strongly typed and declarative. In this talk, we'll learn how combining these two technologies can lead to massively increased software development and delivery speed, faster APIs, fewer bugs, and ultimately enable you to focus on delivering value on the frontend rather than maintaining three different layers of data models and associated logic on the backend (DB, application, API).

Darrell has recently spent a lot of time in and around the extensible GraphQL validation system. What started as a simple rule to fill a gap in the default rule set, soon turned into a plethora of custom rules to validate every detail of schema business logic in the Neo4j GraphQL Library. He will walk through some basic rules, and demonstrate how the system has been used to implement more complex logic.

In this talk, we're unpacking GraphQL Fusion, a new approach that makes building distributed GraphQL APIs easier. We'll explore how this approach lets your teams work independently by owning different parts of the company's graph and cover how you can reshape subgraphs to follow your company's rules. Come learn about this powerful tool that brings efficiency and customization to your GraphQL operations.

GraphQL is celebrating ever-increasing success in the API zeitgeist: a flexible language for describing precise, consumer-defined queries to data sources in a language capable of describing complex relationships between entities of any shape we can imagine. However, to a developer coming from the world of OData, it may seem quite limited at first: how do I filter my data or build complex aggregations? How do I avoid race conditions when I start changing it?

In this talk, we'll look at the OData specification, and discuss a number of its ideas that (I think) would be worth adopting into the culture of GraphQL. We'll look at the differences between the two ecosystems, the open source projects that try to reconcile those differences, and probably end up inventing a third competing standard along the way.