Every year we conduct two global, independent developer surveys engaging more than 30,000 developers. We track development trends across platforms, revenues, apps, tools, languages etc. The 18th Developer Economics survey ran from November 2019 to February 2020 with more than 17,000 developers and tech-makers participating, allowing us to analyze and understand development trends on major […]
Which programming languages the developer nation uses the most? Our data reveal which programming language communities are rising faster than others, which are dropping down the rankings, and which are the new additions to the club! Take a look at our infographic containing key findings from our Developer Economics Q4 2019 survey. First of all, […]
Some things change and others stay the same. When we looked at our data on what developers were reading in Q2, data and analytics, Jakarta, cloud-native, Kubernetes and Open Source topped the list.
The choice of programming language matters deeply to developers because they want to keep their skills up to date and marketable. Languages are a beloved subject of debate and the kernels of some of the strongest developer communities. They matter to toolmakers too, as they want to make sure they provide the most useful SDKs.
Our semi-annual Developer Economics survey is now LIVE! Don’t miss a chance to join over 40,000 developers from 160+ countries who take part in our surveys every year to tell us about trends and shape the future of where software development is going next.
Q&A sites and data science forums are buzzing with the same questions over and over again: I’m new in data science, what language should I learn? What’s the best language for machine learning?
Have a look at this infographic about the Developer Economics: Developer Tools Benchmarking survey, check the numbers and you will be able to find out how it has come to be the most global developer survey.
In recent years artificial intelligence (AI) has returned to the forefront of technological debate. That debate has moved on from when, and even whether, computers will ever display intelligent behaviour to how smart they will get, how quickly, and what the implications are for society. Although there are multiple approaches to creating AIs, the ones that involve machine learning from large datasets are generally outperforming all others.