![]() ![]() Through DataGraph new business services, offerings, and subscription models are explored. Once REST APIs are unified in the Anypoint DataGraph schema, the end users can use any reporting tool of their choice (which supports GraphQL) and create reports and dashboards based on their needs. I tried it with Grafana Cloud and the experience was amazing! One super cool side effect of using Anypoint DataGraph with GraphQL is, that you can use the DataGraph schema and integrate it with any reporting tool, which supports GraphQL as a data source. ![]() In my last article, I have explained the powerful capabilities of MuleSoft Anypoint DataGraph. But basically, you can consume any reporting tool of your choice which supports #graphql endpoints as data sources. In this article, I will describe, how you can connect MuleSoft Anypoint DataGraph with Grafana Labs to create amazing and insightful dashboards. And your developers do not necessarily need to implement all requirements for custom reports, you could hand over a DataGraph endpoint. Tools they typically use for their teams like #tableau, #microsoft #powerbi, #qlik, #grafana, and others. Yes within your application, portal, mobile app, report creation becomes super simple, but you can also provide this endpoint to your end users and they can use the reporting tool of their choice by using #graphql query language. Namely the reporting and dashboarding use case. Select all REST APIs you want to unify and include them into a DataGraph schema, once the process is completed, you will receive a DataGraph endpoint, which can be consumed through GraphQL.īesides all the ease it provides to developers to access data and reduce the heavy lifting on the frontend, I want to discuss another use case. ![]() The question is, how can I migrate my flat-file-based data sources to relational databases? In other words, how can I unify specific REST APIs in order to be able to query data from? The solution is MuleSoft Anypoint DataGraph, without a single line of code. And GraphQL endpoint makes this data available similar to a relational database, specifically through a query language. If I need additional data, I need to consume (open) another REST API resource (flat-file). I know the analogy might not be fair, but on a very abstract level, REST API resources are very much similar to flat files, which includes data I want to consume. Remember, when relational databases were introduced, how much relief they brought to software engineers. Think about the old days and the flat-file-based data sources. ![]()
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