13 Nov 2017
10 software development technologies to learn in 2017
With each passing year, new exciting technologies are making impact in the software development industry. At the same time, well-established languages, frameworks and systems are all competing for our attention, defending their strong positions or gradually falling into oblivion. Our list of top 10 software development technologies to learn in 2017 includes both industry behemoths and newcomers. They all have one thing in common – they’re doing great in the year 2017.
Software development is an ever-changing field – there are few clichés as true as this one. Both budding developers and veterans of all specializations are constantly updating their technology stacks. Sometimes, it is curiosity that drives them to learn new technologies. At other times, the goal is to obtain more marketable skills or simply to meet the requirements of a new project.
Our list is meant to be helpful for all developers. It includes technologies that in the past severals months (or years) have been giving us every right to believe that their popularity is assured and likely not to slow down in the upcoming years. It is also a great way to spot or confirm popular industry trends. Do they show in our list? Let’s find out.
How did we choose our top 10 technologies to learn in 2017 list?
The main basis for our selection was the Stack Overflow Trends tool, which allows you to see the popularity of various technologies over time based on the use of tags associated with them by SO users. While this is by no means a perfect method (for example, technologies blessed with very solid documentation may receive fewer questions since users can find their answers themselves more easily), it does allow you to see how the popularity of any technology changes over time and, roughly, how it compares to other technologies. We also used the Tiobe Index to help shape our list. The index uses data from search engines to determine the popularity of technologies, but it’s only limited to programming languages. We picked the most popular technologies – let’s go over them one by one.
Golden oldies – they are here to stay
Perhaps the most controversial addition to our list. While it is still one of the most ubiquitous programming languages, popular in both web applications and large-scale business systems, some believe that its popularity is in decline. The Tiobe index seemingly confirms it. However, a closer look at the popularity of Java over time shows that there are very technologies that managed to stay consistently at the very top for such a long time. Even today Java remains one of the most popular and talked about programming languages and will likely remain one for a long time, as other technologies come and go.
The Python programming language continues to rank among the most popular technologies. No wonder – this object-oriented language is known for code reliability and brevity and is increasingly popular as a language of choice for entry-level computer science classes at universities. It is also widely used as a scientific scripting language as well as a popular web language.
R is both a programming language and an environment specialized in statistical computing. Conceived back in 1993, it’s by no means new. Its steady rise in popularity in the past few years, however, is a testament to how popular technologies used for data science and big data are becoming. The trend is very likely to continue in the future.
The stars of today – to make a really strong impact
This Apache project made for processing of large data sets across big clusters of computers has quickly become one of the most popular of its kind. And it continues to be a popular technology among SO users despite the rise in popularity of another big data framework from Apache – Spark. However, Apache Spark isn’t exactly a replacement for Hadoop and these two frameworks can be used together. Hence, it’s very much worth your effort as big data continues to be one of the hottest trends in the entire IT industry.
8. Apache Spark
And so is Apache Spark. Its advanced analytical capabilities can take your ability to process large data sets to a new level.
New kids on the block
Well, not exactly new, but it was only in the last two years when their popularity really skyrocketed. And that’s not too big of a word by any stretch of the imagination – both technologies performed spectacularly and are expected to do even better in the upcoming months.
The growing popularity of TensorFlow, an open source library from Google for machine learning applications, is yet another proof of just how serious companies are becoming about practical applications of machine learning algorithms.
What do you think about our list? Which technologies we listed are you using? What trends does their popularity uncover? Do you think that some other technologies should have made the list? Let us know in the comment section below. And if you have a software development project of your own you would like us to help with, simply contact us and let us know.