#database

- Errors? How to render and log your server and client errorsa - When to return errors vs throwb - Setup logging service like Sentry, LogRocket, and Bugsnag- Forms? How to validate and handle multi-page formsa - Use zod to validate form data in your actionb - Step through multi-page forms without losing data- Stuck? How to patch bugs or missing features in Remix so you can move ona - Use patch-package to quickly fix your Remix installb - Show tool for managing multiple patches and cherry-pick open PRs- Users? How to handle multi-tenant apps with Prismaa - Determine tenant by host or by userb - Multiple database or single database/multiple schemasc - Ensures tenant data always separate from others

In this workshop, you will set up a local full-stack environment and create a React Native Mobile app that runs against that stack. 
Agenda:- Install Oracle 23ai Docker container- Build and run Parse Server with the new Oracle Storage Adapter - Build and run a Walking History React Native mobile app against the stack
Walking History is a React Native application that allows you to walk around New York City (or simulate that in a device emulator) and it tells you about the closest attraction or point of interest.



The database can be one of the hardest parts of a web app to scale. Many projects end up using ad-hoc caching systems that are complex, error-prone, and expensive to build. What if you could drop in a ready-built caching system to enable better throughput and latency with no code changes to your application?
Join developers Aspen Smith and Nick Marino to see how you can change one line of config in your app and use ReadySet to scale up your query performance by orders of magnitude today.

Supabase and Remix make building fullstack apps easy. In this workshop, we are going to learn how to use Supabase to implement authentication and authorization into a realtime Remix application. Join Jon Meyers as he steps through building this app from scratch and demonstrating how you can harness the power of relational databases!

Welcome to Fauna! This workshop helps GraphQL developers build performant applications with Fauna that scale to any size userbase. You start with the basics, using only the GraphQL playground in the Fauna dashboard, then build a complete full-stack application with Next.js, adding functionality as you go along.

In the first section, Getting started with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.

In the second section, Building with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.

YugateDB is a popular open-source Distributed SQL database designed and built for cloud native applications from the ground up. YugateDB allows developers to easily scale the RDBMS workloads for internet-scale apps while natively handling the cloud infrastructure outages supporting cross-region and cross Datacenter deployments. In this workshop, participants will get firsthand experience implementing GraphQL applications using three of the most popular GraphQL engines in Hasura, Prisma, and Spring GraphQL connected to the YugateDB database.

This workshop will provide quick start guides for GraphQL developers for getting started with YugateDB. The workshop will include steps for creating a YugateDB database instance, configuring the database for the respective GraphQL engine, and the best practices for writing the GraphQL queries for YugateDB. From this workshop session, developers will know all the main concepts of getting started with YugateDB and GraphQL to solve the business use case at hand using YugateDB.

This workshop will explore how to build GraphQL APIs backed Neo4j, a native graph database. The Neo4j GraphQL Library allows developers to quickly design and implement fully functional GraphQL APIs without writing any resolvers. This workshop will show how to use the Neo4j GraphQL Library to build a Node.js GraphQL API, including adding custom logic and authorization rules.

Table of contents:
- Overview of GraphQL and building GraphQL APIs
- Building Node.js GraphQL APIs backed a native graph database using the Neo4j GraphQL Library
- Adding custom logic to our GraphQL API using the @cypher schema directive and custom resolvers
- Adding authentication and authorization rules to our GraphQL API

In this workshop we'll dig deeper into data modeling. We'll start with a discussion about various database types and how they map to GraphQL. Once that groundwork is laid out, the focus will shift to specific types of databases and how to build data models that work best for GraphQL within various scenarios.
Table of contentsPart 1 - Hour 1      a. Relational Database Data Modeling      b. Comparing Relational and NoSQL Databases      c. GraphQL with the Database in mindPart 2 - Hour 2      a. Designing Relational Data Models      b. Relationship, Building MultijoinsTables      c. GraphQL & Relational Data Modeling Query Complexities
Prerequisites      a. Data modeling tool. The trainer will be using dbdiagram      b. Postgres, albeit no need to install this locally, as I'll be using a Postgres Dicker image, from Docker Hub for all examples      c. Hasura

InfluxDB is an open source time series database that empowers developers to build IoT, analytics and monitoring software. It is purpose-built to handle the massive volumes and countless sources of time-stamped data produced sensors, applications and infrastructure.
This workshop showcases a fully functional sample application called IoT Center that is built on InfluxDB. This application demonstrates the capabilities of the InfluxDB platform to develop a JavaScript-enabled time-series-based application. It collects, stores and displays a set of values that include temperature, humidity, pressure, CO2 concentration, air quality, as well as provide GPS coordinates from a set of IoT devices. With this data stored in InfluxDB, the application can query this data for display as well as write data back into the database.
This hands-on workshop will show students how to install this open source code to learn how to query and write to InfluxDB using the InfluxDB JavaScript client, and gain familiarity with the Flux lang query language which is designed for querying, analyzing, and acting on time series data. And finally, collect and visualize performance data of the Node JS application.