It was conceived in 2012 by Facebook and then popularised by big players like GitLab, Pinterest and Shopify, after its release to the public in 2015. GraphQL is a specification for a query language for your APIs. Allow me to take a step back and take you through a short overview of GraphQL. Traditional REST may not be enough, but pairing it with a relational spec might be the answer. SO WHAT CAN BE DONE TO REDUCE OR AVOID THESE EFFORTS ALTOGETHER? sieving through all of the API’s response fields – not just the ones that you need.writing custom code to parse the responses from each API.writing custom code to fire requests to each API.Attached to this comes the need for significant additional effort, in the form of: What’s interesting is that in most scenarios the consumers of said REST APIs are likely to require data to come from several ones at a time. “Rest” assured (pun intended!), REST APIs and API-led connectivity are still the foundation that every company needs to get right in order to efficiently drive reuse of assets and unlock their data. MuleSoft Composer and Anypoint DataGraph are two new products that promise to accelerate integration in new ways that go beyond the traditional programmatic consumption of REST APIs. This year we’ve seen MuleSoft make some exciting additions to its offering. I will then discuss Anypoint DataGraph’s role in the context of MuleSoft’s own evangelised API-led connectivity, closing with an evaluation of the product’s capabilities, limitations and gotchas. I will set the scene by describing the use cases that Anypoint DataGraph tries to address, as well as the specification upon which it is built: GraphQL. MuleSoft gave us a lot to think about and tinker with last year by launching two brand new products: MuleSoft Composer and Anypoint DataGraph.
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