Have you ever faced the task of implementing a REST API and had to call multiple endpoints to populate data for a single screen? You probably wished you had more control over the data returned by the endpoint so that you could fetch more data with a single endpoint call or have only the necessary data fields returned by the call. Follow along to see how you can achieve this with GraphQL. In this article, we’ll be implementing GraphQL in an existing codebase.
In this tutorial, we will share some hands-on experience on how to use the AWS Lambda, learn to design and build a Serverless function to trigger Bitrise builds with Bitrise API via the custom Lambda function.
In our previous post, we discussed the benefits and drawbacks of two of the most popular API models – REST and gRPC. In this post, we’ll highlight the final API model in our series, GraphQL. Finally, we’ll recap our learnings with a side-by-side comparison of REST, gRPC and GraphQL.
In today’s digital world, every savvy marketer knows that video marketing is essential in overall digital campaigns. They make sure that they constantly come up with ideas to create new video content. But, as a marketer yourself, you know that creating new video content every month or even week is not only costly but also time-consuming and backbreaking. This is where repurposing the old video content you have is such an exciting idea.
How policies, processes, roles and technology come together to ensure data integrity, data quality and access control.
In 2010, Eric Schmidt, then CEO of Google, made the startling claim that every two days we humans generate as much information as we did from the dawn of civilization to today, or about five exabytes of data. At the time, we had TB disk drives and could only imagine an exabyte, which is one million terabytes. The next increments from TB is the peta byte and then the zettabyte, which is 1,000 exabytes. By the end of 2010, the world had crossed the zettabyte threshold.
