Accelerating Application Development with GraphQL Data Mesh

GraphQL Data Mesh can accelerate application development by allowing data to be shared for analytical purposes in real-time, right at the point of origin.

• Data Mesh is an emerging concept focused on moving analytical data away from a monolithic data warehouse or data lake into a distributed architecture
• GraphQL can be a powerful solution for data and application modernization problems for both operational and analytical data
• GraphQL provides a semantic JSON model, speed of light caching, and security and authorization
• GraphQL is a query language for APIs, closer to SQL than a collection of endpoints
• GraphQL has modern primitives like subscriptions for consuming real-time data and streams of data
• GraphQL schema is a built-in artifact

GraphQL condenses the multiple API calls problem into a single API call, making it easier for API users to discover and consume APIs. It also allows for creating a flexible API that does things like pagination, aggregations, joins, and cursor-based sorting in a more coherent query language type structure. Additionally, GraphQL's built-in schema makes it introspectible, similar to a database, allowing for easier management of data models.

The Data Mesh is an emerging concept focused on moving analytical data away from a monolithic data warehouse or data lake into a distributed architecture, allowing data to be shared for analytical purposes in real-time, right at the point of origin. When mixed with GraphQL, it can be a very powerful solution for some of the most pressing challenges that application developers face today. Attendees will learn about the concept of a data mesh and the benefits of using it as a solution to data and application modernization problems for both operational and analytical data. They will also learn about best practices in building, operating and maintaining an enterprise-grade data mesh architecture powered by GraphQL.