1. The document discusses GraphQL, an API query language created by Facebook. It introduces GraphQL concepts like queries, mutations, and subscriptions.
2. An example compares fetching data from a REST API versus a GraphQL API. GraphQL allows fetching all required data with a single request, whereas REST requires multiple requests.
3. React and GraphQL are a good fit because GraphQL is declarative, allowing developers to focus on what data is needed rather than how to fetch it. Popular GraphQL clients like Apollo make fetching data even more declarative.
GraphQL has grown out of its baby shoes and is becoming the new standard for client-server communication. When it was introduced 2 years ago, there merely was any tooling that would help developers using it except for Facebook's reference implementation in JavaScript as well as corresponding middleware for Express so you could embed it in your web server. By now, the situation has changed drastically and a plethora of tools, libraries and services have entered the GraphQL ecosystem, providing great improvements to workflows and overall developer experience. In this talk, Nikolas will give an overview of the most relevant tools that exist in the GraphQL ecosystem today, ensuring you can make the best choices when starting your own GraphQL journey.
Kafka and GraphQL: Misconceptions and Connections | Gerard Klijs, Open WebHostedbyConfluent
GraphQL is a powerful way to bridge the gap between frontend and backend. Providing a typed API with introspection. This can be used for code generation or code completion.
Because of some misconceptions it can be hard to combine GraphQL with Kafka, but it doesn’t need to be hard.
After handling misconceptions like 'Kafka is just a message bus' and 'GraphQL is only for Graph databases' I will have a few demo's how both can be combined. It can be a clear way to make your event sourcing backend available to the frontend. GraphQL can be used to quickly setup a typed API, if you already use ksqlDB.
Taking Control of your Data with GraphQLVinci Rufus
The document discusses how GraphQL provides a solution for problems with traditional REST APIs by allowing flexible data fetching with one query. It summarizes pain points like over-fetching or under-fetching data and inconsistent features between platforms. The document then explains what GraphQL is, how it evolved from internal use at Facebook, popular brands using it, its specifications and implementations in different languages. It demonstrates how GraphQL enables flexible querying of data without versioning or multiple endpoints. The document also covers related tools like GraphiQL, schemas and types, and how GraphQL can be used with React. It concludes by discussing upcoming areas of focus like prioritizing data and supporting real-time updates.
Meteor MIT Tech Talk 9/18/14: Designing a New Platform For Modern AppsSashko Stubailo
These are the slides for the talk Emily Stark and I presented at MIT on September 9, 2014.
We talked about the components that make up Meteor and how they fit together, finishing off with a more in-depth discussion of DDP, Meteor's Distributed Data Protocol.
Wrapping and Securing REST APIs with GraphQLRoy Derks
The document discusses building a GraphQL API that fetches data from REST endpoints. It describes using JSON web tokens (JWT) for authentication by passing them in request headers to the REST API. It also discusses using Apollo data sources, which help with caching requests and fetching authentication data from request headers to pass to REST APIs. The document provides examples of building a GraphQL server with Express and Apollo that implements these techniques.
This document discusses how Angular2 aims to make applications fast and lean. It highlights several techniques Angular2 uses such as ahead-of-time compilation, lazy loading of routes, unidirectional data flow, and tree shaking that help reduce bundle size and improve performance. Universal rendering is also discussed as a way to eliminate the initial loading delay by pre-rendering pages on the server.
In this talk, we shared some of our highlights of the GraphQL Europe conference.
You can see the full coverage of the conference here: https://www.graph.cool/talks/
GraphQL Munich Meetup #1 - How We Use GraphQL At CommercetoolsNicola Molinari
The document describes commercetools' experience with adopting GraphQL for their merchant center application. They were initially fetching category data with multiple REST requests, but were able to fetch it in one GraphQL query along with additional fields like number of subcategories and products. This solved a performance issue and allowed them to easily extend their API. They also migrated other parts of their client to use GraphQL, reducing network requests and complexity. Overall, GraphQL allowed them to optimize queries and extend their API with minimal effort.
VulcanJS is a full-stack React and GraphQL framework that aims to provide an opinionated but flexible platform. It offers features like automatic user accounts, schema generation, data loading components, permissions, forms, theming support, server-side rendering, i18n, payments and more out of the box. The framework is updated constantly by its community and aims to help developers get applications from concept to production quickly with fewer resources needed.
The document summarizes an experiment comparing the performance of GraphQL and REST APIs when querying data from MongoDB and ElasticSearch databases. The key findings are:
1) Optimizing queries between the client and application server had less impact than expected, with GraphQL responses being smaller but not significantly faster.
2) Optimizing queries between the application server and databases showed more significant performance gains, with projections in GraphQL and optimized database queries improving speeds.
3) GraphQL's ability to optimize queries from client to data storage is an advantage, but it should not be chosen primarily for performance reasons alone. Further testing is needed to evaluate performance for specific use cases.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Taking Gliffy to the Cloud – Moving to Atlassian Connect - Mike CialowiczAtlassian
To take advantage of Atlassian Connect, the Gliffy team had to re-architect several components of our popular diagramming plugin. Learn about the challenges we faced, how we overcame them, and tips on how you can take your P2 plugin to the cloud.
This document discusses using GraphQL to query Mule4 APIs. It outlines problems with existing integration styles that make multiple requests for different data. GraphQL is introduced as a solution that allows querying for multiple data types in a single request by defining the fields required. The document then covers writing GraphQL code in Mule4, including using a GraphQL router connector, and concludes with a Q&A section.
The document discusses how to use the Batch Update API to synchronize user profile properties between an on-premises Active Directory, an Azure SQL database storing additional user attributes from a line of business system, and SharePoint Online user profiles. It provides an overview of the architecture for syncing data across these systems using PowerShell, an Azure web job, and the Batch Update API to queue updates and check job status. Code samples and resources are also referenced.
The document outlines 10 things to know about Postman, an API development tool. It lists features like running API calls easily with an HTTP client, visualizing response data, debugging with the console, intercepting cookies, controlling code generation, testing APIs, integrating with continuous deployment, collaborating with teams, maintaining API specifications, and publishing APIs. The document encourages providing feedback to help improve Postman.
A Link Generator for Increasing the Utility of OpenAPI-to-GraphQL TranslationsIstvanKoren
The document describes an automatic link generator tool for OpenAPI specifications. It summarizes that GraphQL is gaining popularity as an alternative to REST APIs, but migrating existing REST APIs to GraphQL via tools like OpenAPI-to-GraphQL results in GraphQL schemas that lack connections between related resources. The presented link generator analyzes OpenAPI paths to identify hierarchical relationships and adds the missing link definitions to better integrate resources in the generated GraphQL schema. The tool has been tested on over 1500 real-world API specifications and was able to add links for about 34% of them.
Py conkr 2020-automated newsletter service for your valuable community-chans...Park Chansung
This document describes an automated newsletter service for the TensorFlow Korea Facebook group. It discusses the characteristics of the group, the planning background for the newsletter, and implementation details. The service collects and analyzes the top posts from the group each week and sends them in an email newsletter to subscribers for free using GitHub Actions and Google Groups. Future plans include categorizing posts by topic using NLP models to improve the user experience.
LinkedIn uses Kafka for log aggregation and monitoring. It ingests over 500,000 metrics per minute from applications into Kafka, which then writes to storage clusters. It also uses Kafka to transport log data to ELK (Elasticsearch, Logstash, Kibana) for real-time search, analysis and visualization of metrics and logs. Kafka provides benefits like horizontal scalability, multiple consumer groups, and no overhead on client applications.
This document discusses integrating Ember.js frontend applications with Rails backends. It provides a brief introduction to Ember.js and its history alongside Rails. It then introduces the EmberCLI Rails gem, which aims to bridge EmberCLI and Rails by handling shared responsibilities like API testing generators and asset compilation/serving to provide a unified development experience. The goals of the gem are to avoid issues of complete separation between frontend and backend while maintaining their separation of concerns.
Presented at ServerlessConf NYC 2016.
There are a number of open source projects built around closed platforms like AWS Lambda/Google Cloud Functions and open serverless projects like OpenWhisk and LeverOS. In this talk we'll cover what motivates contributors, what sends them running the other direction, and how you can help your project grow. Building a project on top of closed technology is an extra challenge without insight into where it's going. Learn how to manage continuous integration with your project against your (closed) dependencies and make sure bugs stay fixed.
Artsem Semianenko (Adform) - "Flink in action или как приручить белочку"
Slides for presentation: https://www.youtube.com/watch?v=YSI5_RFlcPE
Source: https://github.com/art4ul/flink-demo
This document discusses GraphQL, a query language for APIs and a runtime for fulfilling queries with existing data. It provides examples of basic queries, nested fields, connections, arguments, and fragments. It also covers GraphQL types including scalars, schemas, definitions, predicates, and data resolution. GraphQL allows clients to define the structure of the data required, and specifies querying, modifying, and transmitting data between client and server.
AtlasCamp 2014: Collaboration State of the UnionAtlassian
Confluence has an all new REST API and a host of other improvements for developers. Now it's even easier to build amazing extensions to Confluence, whether it's with Atlassian Connect or our Plugin SDK. Learn what our Confluence engineers have been working on and what's coming up for Confluence in the next year.
Reactive streams and components on OSGi - C Schneidermfrancis
OSGi Community Event 2017 Presentation by Christian Schneider [Adobe]
Reactive frameworks allow to implement non blocking asynchronous processing in a convenient way. This talk explores how to apply reactive patterns to typical use cases on OSGi like REST services, MQTT Message processing, computations over sliding windows.
We combine messaging and reactor.io streams like also used in Spring 5 to create services that are highly scalable while not tying the user to the technologies being used.
The presented reactive components framework allows to abstract from the messaging technologies using OSGi services. These offer standard Publishers and Subscribers that work nicely with any reactive framework based on the reactive streams API.
This allows to create integrations like with Apache Camel but in a much leaner and OSGi compliant way.
Streaming Data Integration - For Women in Big Data MeetupGwen (Chen) Shapira
A stream processing platform is not an island unto itself; it must be connected to all of your existing data systems, applications, and sources. In this talk, we will provide different options for integrating systems and applications with Apache Kafka, with a focus on the Kafka Connect framework and the ecosystem of Kafka connectors. We will discuss the intended use cases for Kafka Connect and share our experience and best practices for building large-scale data pipelines using Apache Kafka.
1. The document introduces serverless GraphQL backends using Graphcool, a framework that allows building serverless GraphQL APIs.
2. Key features of Graphcool include automatically generating CRUD APIs from a data model, an event-driven core to implement business logic, and global type safety defined by the GraphQL schema.
3. Serverless functions in Graphcool can be used to implement subscriptions that trigger asynchronous events, as well as custom resolvers for queries and mutations.
This document provides an introduction and overview of GraphQL, including examples of how GraphQL compares to REST for fetching data from an API. Key points include:
- GraphQL is a new API query language created by Facebook that allows clients to fetch and update data in a declarative way.
- GraphQL allows clients to fetch multiple related data types in one request, whereas REST typically requires multiple endpoints and requests.
- The document demonstrates building a blogging app example using REST versus GraphQL to fetch user, post, and follower data.
- Other GraphQL concepts covered include mutations for writing data, query variables, subscriptions for real-time updates, and exploring GraphQL with a playground.
-
GraphQL Munich Meetup #1 - How We Use GraphQL At CommercetoolsNicola Molinari
The document describes commercetools' experience with adopting GraphQL for their merchant center application. They were initially fetching category data with multiple REST requests, but were able to fetch it in one GraphQL query along with additional fields like number of subcategories and products. This solved a performance issue and allowed them to easily extend their API. They also migrated other parts of their client to use GraphQL, reducing network requests and complexity. Overall, GraphQL allowed them to optimize queries and extend their API with minimal effort.
VulcanJS is a full-stack React and GraphQL framework that aims to provide an opinionated but flexible platform. It offers features like automatic user accounts, schema generation, data loading components, permissions, forms, theming support, server-side rendering, i18n, payments and more out of the box. The framework is updated constantly by its community and aims to help developers get applications from concept to production quickly with fewer resources needed.
The document summarizes an experiment comparing the performance of GraphQL and REST APIs when querying data from MongoDB and ElasticSearch databases. The key findings are:
1) Optimizing queries between the client and application server had less impact than expected, with GraphQL responses being smaller but not significantly faster.
2) Optimizing queries between the application server and databases showed more significant performance gains, with projections in GraphQL and optimized database queries improving speeds.
3) GraphQL's ability to optimize queries from client to data storage is an advantage, but it should not be chosen primarily for performance reasons alone. Further testing is needed to evaluate performance for specific use cases.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Taking Gliffy to the Cloud – Moving to Atlassian Connect - Mike CialowiczAtlassian
To take advantage of Atlassian Connect, the Gliffy team had to re-architect several components of our popular diagramming plugin. Learn about the challenges we faced, how we overcame them, and tips on how you can take your P2 plugin to the cloud.
This document discusses using GraphQL to query Mule4 APIs. It outlines problems with existing integration styles that make multiple requests for different data. GraphQL is introduced as a solution that allows querying for multiple data types in a single request by defining the fields required. The document then covers writing GraphQL code in Mule4, including using a GraphQL router connector, and concludes with a Q&A section.
The document discusses how to use the Batch Update API to synchronize user profile properties between an on-premises Active Directory, an Azure SQL database storing additional user attributes from a line of business system, and SharePoint Online user profiles. It provides an overview of the architecture for syncing data across these systems using PowerShell, an Azure web job, and the Batch Update API to queue updates and check job status. Code samples and resources are also referenced.
The document outlines 10 things to know about Postman, an API development tool. It lists features like running API calls easily with an HTTP client, visualizing response data, debugging with the console, intercepting cookies, controlling code generation, testing APIs, integrating with continuous deployment, collaborating with teams, maintaining API specifications, and publishing APIs. The document encourages providing feedback to help improve Postman.
A Link Generator for Increasing the Utility of OpenAPI-to-GraphQL TranslationsIstvanKoren
The document describes an automatic link generator tool for OpenAPI specifications. It summarizes that GraphQL is gaining popularity as an alternative to REST APIs, but migrating existing REST APIs to GraphQL via tools like OpenAPI-to-GraphQL results in GraphQL schemas that lack connections between related resources. The presented link generator analyzes OpenAPI paths to identify hierarchical relationships and adds the missing link definitions to better integrate resources in the generated GraphQL schema. The tool has been tested on over 1500 real-world API specifications and was able to add links for about 34% of them.
Py conkr 2020-automated newsletter service for your valuable community-chans...Park Chansung
This document describes an automated newsletter service for the TensorFlow Korea Facebook group. It discusses the characteristics of the group, the planning background for the newsletter, and implementation details. The service collects and analyzes the top posts from the group each week and sends them in an email newsletter to subscribers for free using GitHub Actions and Google Groups. Future plans include categorizing posts by topic using NLP models to improve the user experience.
LinkedIn uses Kafka for log aggregation and monitoring. It ingests over 500,000 metrics per minute from applications into Kafka, which then writes to storage clusters. It also uses Kafka to transport log data to ELK (Elasticsearch, Logstash, Kibana) for real-time search, analysis and visualization of metrics and logs. Kafka provides benefits like horizontal scalability, multiple consumer groups, and no overhead on client applications.
This document discusses integrating Ember.js frontend applications with Rails backends. It provides a brief introduction to Ember.js and its history alongside Rails. It then introduces the EmberCLI Rails gem, which aims to bridge EmberCLI and Rails by handling shared responsibilities like API testing generators and asset compilation/serving to provide a unified development experience. The goals of the gem are to avoid issues of complete separation between frontend and backend while maintaining their separation of concerns.
Presented at ServerlessConf NYC 2016.
There are a number of open source projects built around closed platforms like AWS Lambda/Google Cloud Functions and open serverless projects like OpenWhisk and LeverOS. In this talk we'll cover what motivates contributors, what sends them running the other direction, and how you can help your project grow. Building a project on top of closed technology is an extra challenge without insight into where it's going. Learn how to manage continuous integration with your project against your (closed) dependencies and make sure bugs stay fixed.
Artsem Semianenko (Adform) - "Flink in action или как приручить белочку"
Slides for presentation: https://www.youtube.com/watch?v=YSI5_RFlcPE
Source: https://github.com/art4ul/flink-demo
This document discusses GraphQL, a query language for APIs and a runtime for fulfilling queries with existing data. It provides examples of basic queries, nested fields, connections, arguments, and fragments. It also covers GraphQL types including scalars, schemas, definitions, predicates, and data resolution. GraphQL allows clients to define the structure of the data required, and specifies querying, modifying, and transmitting data between client and server.
AtlasCamp 2014: Collaboration State of the UnionAtlassian
Confluence has an all new REST API and a host of other improvements for developers. Now it's even easier to build amazing extensions to Confluence, whether it's with Atlassian Connect or our Plugin SDK. Learn what our Confluence engineers have been working on and what's coming up for Confluence in the next year.
Reactive streams and components on OSGi - C Schneidermfrancis
OSGi Community Event 2017 Presentation by Christian Schneider [Adobe]
Reactive frameworks allow to implement non blocking asynchronous processing in a convenient way. This talk explores how to apply reactive patterns to typical use cases on OSGi like REST services, MQTT Message processing, computations over sliding windows.
We combine messaging and reactor.io streams like also used in Spring 5 to create services that are highly scalable while not tying the user to the technologies being used.
The presented reactive components framework allows to abstract from the messaging technologies using OSGi services. These offer standard Publishers and Subscribers that work nicely with any reactive framework based on the reactive streams API.
This allows to create integrations like with Apache Camel but in a much leaner and OSGi compliant way.
Streaming Data Integration - For Women in Big Data MeetupGwen (Chen) Shapira
A stream processing platform is not an island unto itself; it must be connected to all of your existing data systems, applications, and sources. In this talk, we will provide different options for integrating systems and applications with Apache Kafka, with a focus on the Kafka Connect framework and the ecosystem of Kafka connectors. We will discuss the intended use cases for Kafka Connect and share our experience and best practices for building large-scale data pipelines using Apache Kafka.
1. The document introduces serverless GraphQL backends using Graphcool, a framework that allows building serverless GraphQL APIs.
2. Key features of Graphcool include automatically generating CRUD APIs from a data model, an event-driven core to implement business logic, and global type safety defined by the GraphQL schema.
3. Serverless functions in Graphcool can be used to implement subscriptions that trigger asynchronous events, as well as custom resolvers for queries and mutations.
This document provides an introduction and overview of GraphQL, including examples of how GraphQL compares to REST for fetching data from an API. Key points include:
- GraphQL is a new API query language created by Facebook that allows clients to fetch and update data in a declarative way.
- GraphQL allows clients to fetch multiple related data types in one request, whereas REST typically requires multiple endpoints and requests.
- The document demonstrates building a blogging app example using REST versus GraphQL to fetch user, post, and follower data.
- Other GraphQL concepts covered include mutations for writing data, query variables, subscriptions for real-time updates, and exploring GraphQL with a playground.
-
GraphQL Schema Stitching with Prisma & ContentfulNikolas Burk
GraphQL schema stitching allows combining multiple GraphQL APIs into a single API. It uses schema delegation under the hood. Prisma is a GraphQL API layer that can be used to stitch a headless Contentful CMS with a database. This provides a unified GraphQL API and makes building complex apps and managing content easier. The presentation demonstrated exploring Contentful's GraphQL API with bindings, auto-generated clients, and stitching Contentful to a database with Prisma.
Building GraphQL Servers with Node.JS & PrismaNikolas Burk
This document discusses building GraphQL servers with Node.js and Prisma. It introduces GraphQL and its benefits like querying exact data needs. It also outlines the three parts of a GraphQL server: the schema, resolver functions, and network layer. It then provides an example of building a clone of the Medium API from scratch in steps, starting with a minimal GraphQL server and adding database integration with Prisma and completing the API operations. The document encourages following along with the code examples provided in the GitHub repository. It also mentions Prisma is hiring.
This document introduces GraphQL, comparing it to REST. It discusses GraphQL concepts like queries, mutations, and subscriptions. It provides examples of GraphQL queries. It also demonstrates how to implement GraphQL in Node.js and lists GraphQL libraries and third-party services. Live demos are linked to show GraphQL usage.
CONDG April 23 2020 - Baskar Rao - GraphQLMatthew Groves
This document provides an overview of GraphQL, including:
- A brief history of API architectures like REST and how GraphQL compares
- Common problems with REST APIs that GraphQL aims to address
- Key aspects of GraphQL like queries, mutations, subscriptions and its schema-first approach
- Popular GraphQL platforms and clients like Apollo, Hasura and Relay
- A demo of building a GraphQL API
GraphQL and its schema as a universal layer for database accessConnected Data World
GraphQL is a query language mostly used to streamline access to REST APIs. It is seeing tremendous growth and adoption, in organizations like Airbnb, Coursera, Docker, GitHub, Twitter, Uber, and Facebook, where it was invented.
As REST APIs are proliferating, the promise of accessing them all through a single query language and hub, which is what GraphQL and GraphQL server implementations bring, is alluring.
A significant recent addition to GraphQL was SDL, its schema definition language. SDL enables developers to define a schema governing interaction with the back-end that GraphQL servers can then implement and enforce.
Prisma is a productized version of the data layer leveraging GraphQL to access any database. Prisma works with MySQL, Postgres, and MongoDB, and is adding to this list.
Prisma sees the GraphQL community really coming together around the idea of schema-first development, and wants to use GraphQL SDL as the foundation for all interfaces between systems.
React, GraphQL и Relay - вполне себе нормальный компонентный подход (nodkz)Pavel Chertorogov
The document discusses React, Relay, and GraphQL. It describes them as a "quite normal component approach" and provides overviews of each technology. For GraphQL, it highlights how GraphQL allows for single requests with nested data and any combinations of backend data sources. For Relay, it explains how Relay correlates components with GraphQL types and fragments to define necessary fields and render instructions. Live demos of a GraphQL server and Relay app are also referenced.
It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time
This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects
The Serverless GraphQL Backend ArchitectureNikolas Burk
This document discusses serverless GraphQL backend architectures. It introduces GraphQL concepts like queries, mutations, schemas and resolver functions. It then outlines how a serverless GraphQL backend can be built using automatically generated CRUD APIs from a data model, event-driven business logic via serverless functions, and a global type system defined in the GraphQL schema. It provides Graphcool as an example platform for building serverless GraphQL backends that leverages request pipelines, subscriptions and schema extensions.
GraphQL with .NET Core Microservices.pdfKnoldus Inc.
In this Webinar, will talk on GraphQL with .NET, that provides a modern and flexible approach to building APIs. It empowers developers to create efficient and tailored APIs that meet the specific needs of their applications and clients.
The document discusses building a realtime chat application with GraphQL subscriptions. It begins with an introduction to GraphQL and an example of how a blogging application's data could be modeled with GraphQL queries. It then covers how realtime updates can be implemented with GraphQL subscriptions. The remainder discusses building a chat application with React, Apollo Client, and server-side subscriptions using Graphcool.
This document discusses the evolution of APIs from REST to GraphQL. It begins by describing RESTful microservices and their limitations in needing multiple requests to retrieve related data. Next, it introduces GraphQL as providing a better solution through allowing clients to request specific data in a single query using a defined schema. The document provides an example GraphQL query and describes how Apollo GraphQL can be used to create a GraphQL server and support federated data. It concludes by noting GraphQL addresses issues with REST by being faster, requiring less data transfer and hosting costs, and through integrated development tools.
GraphQL is quickly becoming mainstream as one of the best ways to get data into your React application. When we see people modernize their app architecture and move to React, they often want to migrate their API to GraphQL as part of the same effort. But while React is super easy to adopt in a small part of your app at a time, GraphQL can seem like a much larger investment. In this talk, we’ll go over the fastest and most effective ways for React developers to incrementally migrate their existing APIs and backends to GraphQL, then talk about opportunities for improvement in the space. If you’re using React and are interested in GraphQL, but are looking for an extra push to get it up and running at your company, this is the talk for you!
A small attempt to deliver a session on GraphQL Introduction.
I have prepared small Demo by using below technologies: Spring Boot, h2 Database (Server)
Angular 8, Apollo GraphQL Client
This document introduces Camunda GraphQL, which provides a GraphQL API for the Camunda platform. It discusses what GraphQL is and how it can be used with Camunda. The architecture of Camunda GraphQL is presented, showing how GraphQL clients connect to the shared process engine. Demos then showcase the benefits of GraphQL for fetching task and user data efficiently with fewer requests compared to REST. Lastly, opportunities for future development are discussed, such as increasing Java API coverage and using GraphQL for real-time updates and microservices.
Discover how GraphQL can help you building and evolve your business APIs.
GraphQL is a query language for APIs developed internally by Facebook. It allows the developers to ask for exactly what they need and nothing more, making it easier to evolve APIs over time and create powerful developer tools around an API.
Presented by Helder Vasconcelos and Luis Gonçalves on 21st May 2019 @ Reactor Innovation Hub.
Powered by https://taikai.network
This document provides an overview of GraphQL basics and compares it to REST APIs. It discusses that GraphQL allows fetching multiple resources with a single query, while REST typically requires multiple requests. GraphQL also avoids over-fetching and under-fetching of data, and provides built-in type checking and documentation. The document outlines topics that will be covered in the next session, including GraphQL schemas, resolvers, and introspection.
This document provides an overview and agenda for a workshop on building a full stack GraphQL application using Neo4j AuraDB, Next.js, and Vercel. The agenda includes introductions to Neo4j AuraDB, building GraphQL APIs, Next.js, and deploying to Vercel. Hands-on exercises will have attendees create a Neo4j AuraDB instance, build GraphQL APIs backed by Neo4j, develop a Next.js frontend application, and deploy the full stack application to Vercel.
Analytics Web Day | From Theory to Practice: Big Data Stories from the FieldAWS Germany
The document discusses three case studies of companies using big data technologies:
1) An insurance company modernized its data warehouse by using AWS services like S3, EMR and Zeppelin for analytics at minimal cost.
2) A telecom company implemented advanced analytics and stream processing on AWS to better understand customers and enhance systems.
3) An industrial use case uses stream processing, machine learning and AWS services for predictive maintenance and error detection.
Analytics Web Day | Query your Data in S3 with SQL and optimize for Cost and ...AWS Germany
The previous presentation showed how events can be ingested and analyzed continuously in real time. One of Big Data's principles is to store raw data as long as possible - to be able to answer future questions. If the data is permanently stored in Amazon Simple Storage Service (S3), it can be queried at any time with Amazon Athena without spinning up a database.
This session shows step by step how the data should be structured so that both costs and response times are reduced when using Athena. The details and effects of compression, partitions, and column storage formats are compared. Finally, AWS Glue is used as a fully managed service for Extract Transform Load (ETL) to derive optimized views from the raw data for frequently issued queries.
Speaker: Steffen Grunwald, Senior Solutions Architect, AWS
Modern Applications Web Day | Impress Your Friends with Your First Serverless...AWS Germany
"Build and run applications without thinking about servers". You want it? You get it! We will start this session with a motivation why serverless applications are a thing. Once we got there, we will actually start building one, of course with making use of a serverless CI/CD pipeline. After we will have looked into how we can still test it locally, we shall also dive into analyzing and debugging our app - of course in a serverless manner.
Speaker: Dirk Fröhner, Senior Solutions Architect, AWS
Modern Applications Web Day | Manage Your Infrastructure and Configuration on...AWS Germany
It's easy to say - "Hey I will use the cloud and be scalable and elastic!" - But it is not easy managing all that at scale, and keeping it flexible! Let's talk about Infrastructure as Code and Configuration as Code! This session will help you grasp the available toolset and best practices when it comes to managing your infrastructure and configuration on AWS. It will show you how can you make any changes to your workload with a single 'git push origin master'
Speaker: Darko Meszaros, Solutions Architect, AWS
Modern Applications Web Day | Container Workloads on AWSAWS Germany
Containers gained strong traction since day one for both enterprises and startups. Today AWS customers are launching hundreds of millions of new containers – each week. Join us as we cover the state of containerized application development and deployment trends. This session will dive deep on new container capabilities that help customers deploying and running container-based workloads for web services and batches.
Speaker: Steffen Grunwald, Senior Solutions Architect, AWS & Sascha Möllering, Senior Solutions Architect, AWS
Modern Applications Web Day | Continuous Delivery to Amazon EKS with SpinnakerAWS Germany
With more and more application workloads moving to Kubernetes, the interest in managed Kubernetes services in enterprises is increasing. While Amazon EKS will make operations easier, an efficient and transparent delivery pipeline becomes more important than ever. This will provide an increased application development velocity that will directly convert into a competitive advantage with fast paced digital services. While established tools such as Jenkins can be used quite efficiently for CI tasks, modern cloud-native tools like Spinnaker are gaining attention by focusing more in the continuous delivery process. We will show you how Spinnaker and its new Kubernetes v2 provider can be utilized together with Amazon EKS to streamline your application deployments.
Speaker: Jukka Forsgren, nordcloud
The most common way to start developing for Alexa is with custom skills while not too many of us except for device manufacturers get in touch with Smart Home skills on Alexa. This session introduces and demonstrates the power of Smart Home skills and it takes a look behind the technical scene of what happens in between an “Alexa, turn on the lights” and Alexa´s final “Ok” confirmation. Once you are familiar with the concept of Smart Home skills you will find out that it’s not just for implementing large-scale Smart Home solutions as the Smart Home API is also a great playground for your next Do it Yourself project. At the end of this session you’ve learned about the probably simplest way to build a Smart Home project with Raspberry Pi and AWS IoT – and you will be equipped with essential knowledge on how to build your own voice-controlled “thing”.
Hotel or Taxi? "Sorting hat" for travel expenses with AWS ML infrastructureAWS Germany
Automating the boring task of submitting travel expenses we developed ML model for classifying recipes. Using AWS EC2, Lambda, S3, SageMaker, Rekognition we evaluated different ways of training model and serving predictions as well as different model approaches (classical ML vs. Deep Learning).
Wild Rydes with Big Data/Kinesis focus: AWS Serverless WorkshopAWS Germany
This is a hands-on workshop where every participant will not only learn how to architect and implement a serverless application on Amazon Web Services using nothing but serverless resources for all layers in theory, but actually do it in practice, with all the necessary support from the speakers. Serverless computing allows you to build and run applications and services without thinking about servers. Serverless applications don't require you to provision, scale, and manage any servers. You can build them for nearly any type of application or backend service, and everything required to run and scale your application with high availability is handled for you. Building serverless applications means that developers can focus on their core product instead of worrying about managing and operating servers or runtimes. This reduced overhead lets developers reclaim time and energy that can be spent on developing great products which scale and that are reliable.
Nearly everything in IT - servers, applications, websites, connected devices, and other things - generate discrete, time-stamped records of events called logs. Processing and analyzing these logs to gain actionable insights is log analytics. We'll look at how to use centralized log analytics across multiple sources with Amazon Elasticsearch Service.
Deep Dive into Concepts and Tools for Analyzing Streaming Data on AWS AWS Germany
Querying streaming data with SQL to derive actionable insights at the point of impact in a timely and continuous fashion offers various benefits over querying data in a traditional database. However, although it is desirable for many use cases to transition to a stream based paradigm, stream processing systems and traditional databases are fundamentally different: in a database, the data is (more or less) fixed and the queries are executed in an ad-hoc manner, whereas in stream processing systems, the queries are fixed and the data flows through the system in real-time. This leads to different primitives that are required to model and query streaming data.
In this session, we will introduce basic stream processing concepts and discuss strategies that are commonly used to address the challenges that arise from querying of streaming data. We will discuss different time semantics, processing guarantees and elaborate how to deal with reordering and late arriving of events. Finally, we will compare how different streaming use cases can be implemented on AWS by leveraging Amazon Kinesis Data Analytics and Apache Flink.
Zehntausende gemeinnützige und nichtstaatliche Organisationen weltweit verwenden AWS, damit sie sich auf ihre eigentliche Mission konzentrieren können, statt ihre IT-Infrastruktur zu verwalten. Die Anwendungsgebiete von Nonprofits und NGOs sind dabei genauso vielfältig, wie bei Enterprise oder Start-up oder anderen AWS-Anwendern im öffentlichen Sektor. Gemeinnützige Organisationen und NGOs nutzen AWS z.B. um hochverfügbare und hochskalierbare Websites zu erstellen, um ihre Spendenaktionen und Öffentlichkeitsarbeit effizient zu verwalten, oder um Nutzen aus Big Data Anwendungen zu ziehen.
In dieser Sitzung werden wir einen Blick auf die verschiedenen AWS-Programme werfen, die gemeinnützigen Organisationen den Einstige in AWS und die Umsetzung ihrer IT-Projekte erleichtern. Insbesondere informieren wir auch über das Angebote mit Stifter-Helfen.de - dem deutschen TechSoup-Partner. Dieses Angebot stellt den begünstigten Organisationen pro Jahr $2.000 in AWS Credit Codes zu Verfügung.
Die Session richtet sich an alle, die sich für einen guten Zweck engagieren wollen und dabei nicht auf innovative Cloud-Services zur Umsetzung ihrer IT-Projekte verzichten wollen. Für die Teilnahme and der Session sind keine technischen Vorkenntnisse notwendig
The document discusses data architecture challenges and best practices for microservices. It covers challenges like distributed transactions, eventual consistency, and choosing appropriate data stores. It provides recommendations for handling errors and rollbacks in a distributed system using techniques like correlation IDs, transaction managers, and event-driven architectures with DynamoDB streams. The document also provides a framework for classifying non-functional requirements and mapping them to suitable AWS data services.
Serverless vs. Developers – the real crashAWS Germany
With serverless things are getting really different. Commodity building blocks from our cloud providers, functional billing, serverless marketplaces etc. are going to hit the usual “Not invented here”3 syndrome in organizations.
Many beloved things have to be un- or re-learned by software developers. How can we prepare our organizations and people for unlearning old patterns and behaviours? Let’s have a look from a knowledge management perspective.
Objective of the talk:
Intro into systemic knowledge management
Query your data in S3 with SQL and optimize for cost and performanceAWS Germany
Streaming services allow you to ingest and analyze events continuously in real time. One of Big Data's principles is to store raw data as long as possible - to be able to answer future questions. If the data is permanently stored in Amazon Simple Storage Service (S3), it can be queried at any time with Amazon Athena without spinning up a database.
This session shows step by step how the data should be structured so that both costs and response times are reduced when using Athena. The details and effects of compression, partitions, and column storage formats are compared. Finally, AWS Glue is used as a fully managed service for Extract Transform Load (ETL) to derive optimized views from the raw data for frequently issued queries.
Secret Management with Hashicorp’s VaultAWS Germany
When running a Kubernetes Cluster in AWS there are secrets like AWS and Kubernetes credentials, access information for databases or integration with the company LDAP that need to be stored and managed.
HashiCorp’s Vault secures, stores, and controls access to tokens, passwords, certificates, API keys, and other secrets . It handles leasing, key revocation, key rolling, and auditing.
This talk will give an overview of secret management in general and Vault’s concepts. The talk will explain how to make use of Vault’s extensive feature set and show patterns that implement integration between Kubernetes applications and Vault.
Running more than one containerized application in production makes teams look for solutions to quickly deploy and orchestrate containers. One of the most popular options is the open-source project Kubernetes. With the release of the Amazon Elastic Container Service for Kubernetes (EKS), engineering teams now have access to a fully managed Kubernetes control plane and time to focus on building applications. This workshop will deliver hands-on labs to support you getting familiar with Amazon's EKS.
Our challenge is to provide a container cluster as part of the Cloud Platform at Scout24. Our goal is to support all the different applications with varying requirements the Scout24 dev teams can throw at us. Up until now, we have run all of them on the same ECS cluster with the same parameters. As we get further into our AWS migration, we have learned this does not scale. We combat this by introducing categories in one cluster with different configurations for the service. We will introduce how we tune each category differently, with different resource limits, different scaling approaches and more…
Containers gained strong traction since day one for both enterprises and startups. Today AWS customers are launching hundreds of millions of new containers – each week. Join us as we cover the state of containerized application development and deployment trends. This session will dive deep on new container capabilities that help customers deploying and running container-based workloads for web services and batches.
Deploying and Scaling Your First Cloud Application with Amazon LightsailAWS Germany
Are you looking to move to the cloud, but aren’t sure quite where to start? Are you already using AWS, and are looking for ways to simplify some of your workflows? If you answered “yes” (or even “maybe”) to either one of those questions, this session / hands-on workshop is for you. We’re going to take you through using Amazon Lightsail, an AWS service that provides the quickest way to get started in the cloud, to deploy and scale an application on AWS.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...SOFTTECHHUB
I started my online journey with several hosting services before stumbling upon Ai EngineHost. At first, the idea of paying one fee and getting lifetime access seemed too good to pass up. The platform is built on reliable US-based servers, ensuring your projects run at high speeds and remain safe. Let me take you step by step through its benefits and features as I explain why this hosting solution is a perfect fit for digital entrepreneurs.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex
Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how:
• Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules.
• Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance.
• Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity.
• Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications.
• Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market.
With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications.
Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market
For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company
Explore the benefits and features of advanced logistics management software for businesses in Riyadh. This guide delves into the latest technologies, from real-time tracking and route optimization to warehouse management and inventory control, helping businesses streamline their logistics operations and reduce costs. Learn how implementing the right software solution can enhance efficiency, improve customer satisfaction, and provide a competitive edge in the growing logistics sector of Riyadh.
DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptxJustin Reock
Building 10x Organizations with Modern Productivity Metrics
10x developers may be a myth, but 10x organizations are very real, as proven by the influential study performed in the 1980s, ‘The Coding War Games.’
Right now, here in early 2025, we seem to be experiencing YAPP (Yet Another Productivity Philosophy), and that philosophy is converging on developer experience. It seems that with every new method we invent for the delivery of products, whether physical or virtual, we reinvent productivity philosophies to go alongside them.
But which of these approaches actually work? DORA? SPACE? DevEx? What should we invest in and create urgency behind today, so that we don’t find ourselves having the same discussion again in a decade?
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Mobile App Development Company in Saudi ArabiaSteve Jonas
EmizenTech is a globally recognized software development company, proudly serving businesses since 2013. With over 11+ years of industry experience and a team of 200+ skilled professionals, we have successfully delivered 1200+ projects across various sectors. As a leading Mobile App Development Company In Saudi Arabia we offer end-to-end solutions for iOS, Android, and cross-platform applications. Our apps are known for their user-friendly interfaces, scalability, high performance, and strong security features. We tailor each mobile application to meet the unique needs of different industries, ensuring a seamless user experience. EmizenTech is committed to turning your vision into a powerful digital product that drives growth, innovation, and long-term success in the competitive mobile landscape of Saudi Arabia.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies
In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
9. What’s GraphQL?
• New API standard by Facebook
• Query language for APIs
• Declarative way of fetching & updating data
@nikolasburk
10. Mary
Mary’s posts:
Learn GraphQL Today
Why GraphQL is better than
REST
React & GraphQL - A declarative
love story
Relay vs Apollo - GraphQL
clients
Last three followers:
John, Alice, Sarah
Example: Blogging App
11. Example: Blogging App with REST
/users/<id>
/users/<id>/posts
/users/<id>/followers
3 API endpoints
@nikolasburk
12. 1 Fetch user data
/users/<id>/users/<id>
/users/<id>/posts
/users/<id>/followers
{
“user”: {
“id”: “er3tg439frjw”
“name”: “Mary”,
“address”: { … },
“birthday”: “July 26, 1982”
}
}
HTTP GET
Mary
Mary’s posts:
Last three followers:
@nikolasburk
13. 2
/users/<id>
/users/<id>/posts
/users/<id>/followers
Fetch posts
HTTP GET
{
“posts”: [{
“id”: “ncwon3ce89hs”
“title”: “Learn GraphQL today”,
“content”: “Lorem ipsum … ”,
“comments”: [ … ],
}, {
“id”: “dsifr3as0vds”
“title”: “React & GraphQL - A declarative love story”,
“content”: “Lorem ipsum … ”,
“comments”: [ … ],
}, {
“id”: “die5odnvls1o”
“title”: “Why GraphQL is better than REST”,
“content”: “Lorem ipsum … ”,
“comments”: [ … ],
}, {
“id”: “dovmdr3nvl8f”
“title”: “Relay vs Apollo - GraphQL clients”,
“content”: “Lorem ipsum … ”,
“comments”: [ … ],
}]
}
Mary
Mary’s posts:
Learn GraphQL Today
Why GraphQL is better than REST
React & GraphQL - A declarative
love story
Relay vs Apollo - GraphQL clients
Last three followers:
@nikolasburk
14. /users/<id>
/users/<id>/posts
/users/<id>/followers
HTTP GET
{
“followers”: [{
“id”: “leo83h2dojsu”
“name”: “John”,
“address”: { … },
“birthday”: “January 6, 1970”
},{
“id”: “die5odnvls1o”
“name”: “Alice”,
“address”: { … },
“birthday”: “May 1, 1989”
}{
“id”: “xsifr3as0vds”
“name”: “Sarah”,
“address”: { … },
“birthday”: “November 20, 1986”
}
…
]
}
Mary
Mary’s posts:
Learn GraphQL Today
Why GraphQL is better than REST
React & GraphQL - A declarative
love story
Relay vs Apollo - GraphQL clients
Last three followers:
John, Alice, Sarah
Fetch followers3
@nikolasburk
16. Mary’s posts:
Last three followers:
Fetch everything with a single request1
HTTP POST
query {
User(id: “er3tg439frjw”) {
name
posts {
title
}
followers(last: 3) {
name
}
}
}
@nikolasburk
17. Mary’s posts:
Last three followers:
Mary
Learn GraphQL Today
Why GraphQL is better than REST
React & GraphQL - A declarative
love story
Relay vs Apollo - GraphQL clients
John, Alice, Sarah
Fetch everything with a single request1
HTTP POST
{
“data”: {
“User”: {
“name”: “Mary”,
“posts”: [
{ title: “Learn GraphQL today” },
{ title: “React & GraphQL - A declarative love story” }
{ title: “Why GraphQL is better than REST” }
{ title: “Relay vs Apollo - GraphQL Clients” }
],
“followers”: [
{ name: “John” },
{ name: “Alice” },
{ name: “Sarah” },
]
}
}
} @nikolasburk
19. 3 parts of a GraphQL server
1. Structure: The GraphQL schema
2. Behaviour: Resolver functions
3. Network Layer: Network, Middleware, …
20. 1) The GraphQL Schema
• Strongly typed & written in GraphQL Schema Definition
Language (SDL)
• Defines API capabilities ( = contract for client-server
communication)
• Special root types: Query, Mutation, Subscription
@nikolasburk
23. 2) Resolver functions
• Concrete implementation of the API
• One resolver function per field in SDL schema
• Query execution: Invoke resolvers for all fields in query
@nikolasburk