
Are Property Graphs living up to the hype? Maybe the model itself is the problem. We made the move from relational databases to graph databases to escape "Join Pain" and model the real world more naturally — but for many engineering teams, that promise has curdled into something worse: the Spaghetti Graph. Complex queries. Ugly workarounds for multi-party relationships. Fragile schemas that shatter with every iteration and become a nightmare to maintain. The good news? The problem isn't your data. In this talk, Joshua Send breaks down why standard Labeled Property Graphs (LPGs) fall short when applied to complex domains — and introduces TypeDB, a strongly-typed database that brings together the connectivity of a graph with the integrity of a relational model. You'll come away understanding why LPGs struggle at scale and complexity, what "Spaghetti Graphs" are and how teams fall into the trap, how TypeDB's type system enforces data integrity without sacrificing flexibility, and when a strongly-typed graph database is the right tool for the job. Whether you're deep in a graph migration, evaluating database architectures, or just tired of schema chaos — this one's for you.

Multi-account and multi-region compatibility enables users to manage and deploy resources across multiple AWS accounts and geographic regions. This functionality enhances the robustness of the deployments by offering improved fault tolerance, scalability, and regulatory compliance. By segregating resources into separate accounts and distributing them across various regions, users can minimize the impact of potential failures and optimize performance. In this session from LocalStack Community Meetup May '24, Sannya Singhal discussed how you could use LocalStack to emulate multi-account and multi-region environments locally for testing and development purposes, ensuring that applications were resilient and scalable before deployment to the cloud.

LocalStack's cloud emulator lets you run Amazon Elastic Container Service (ECS) clusters and tasks on your local computer. It's sometimes useful to mount code from the host filesystem directly into the ECS container. This helps quickly test changes without needing to rebuild and redeploy the ECS Task's Docker image each time. This video explains how to use code mounting with the ECS bind mounts feature.

We’re partnering with gdotv to simplify development with our Amazon Neptune cloud emulator component. You can now easily query, visualise and model your graph data either interactively or using the Gremlin querying language with G.V() - Gremlin IDE. With G.V(), you can considerably enhance your graph database development experience whilst gaining access to a powerful reporting and visualisation toolset for your production data. With LocalStack’s core cloud emulator, parity is ensured between a local Neptune instance and AWS’s own, meaning Gremlin queries in your development environment will behave identically on Amazon Neptune. In this video we demonstrate how to use G.V() with LocalStack Neptune.