
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.

With the growing Serverless workloads, managing and maintaining them is best recommended with Infrastructure as Code (IaC). While this holds the complete infrastructure and its configurations, we could have events from one service destined to another via configuration. When building these configurations, we could also reduce the application code making it more maintainable and scalable. In this session, Jones walked us through a fully end-to-end solution built with Amazon EventBridge and AWS Step Functions with SDK integrations which have helped him to improvise the application with just IaC and very minimal application code.

Tired of rebuilding your stack from scratch every time you run tests or restart your dev environment? In this episode, we dive into Cloud Pods, LocalStack’s powerful state management feature. You’ll learn how to snapshot your entire LocalStack environment (services, resources, data), restore that exact state across machines, teams, or CI runs, speed up test cycles and workflows, and use Cloud Pods to make testing in CI/CD faster and more reliable. Cloud Pods let you freeze your infrastructure in time. Perfect for repeatable tests, isolated dev environments, or onboarding new teammates.

dbt (Data Build Tool) helps data engineers manage data transformations using modular SQL and brings version control, testing, and documentation to their transformation logic. However, running dbt against production data warehouses like Snowflake can be slow, expensive, and risky. This session introduces a new way to develop and test dbt workflows locally using the Snowflake emulator in LocalStack. You'll learn how to set up a local dbt environment, configure dbt to connect to the Snowflake emulator, run and validate dbt models locally without using a real Snowflake account, and iterate quickly on transformations before pushing them to production. Through a hands-on factory app example, we’ll walk through how to use the Snowflake emulator to run dbt models on your laptop, helping you test logic, catch issues early, and reduce cloud costs.