The rise of nearshoring has seen competition between global tech hubs intensify in recent years. Unlike outsourcing, where an emphasis is placed on cost-saving, nearshoring locations must offer closer working relationships, access to the very best tech skills and strong cultural alignment.
Neueda has earned the enviable reputation of building world-class software development teams, rich with in-depth domain knowledge. Unlike other companies that may specialise in just one or two technologies or languages, we see the value in using the right technology for a given challenge. As such, we’re committed to employing a wide range of technologies, platforms and languages to foster better outcomes for our clients.
Here, we take a closer look at some of the cutting-edge technology and languages we use to ensure we remain a top nearshoring partner for our clients.
Java has developed a massive ecosystem of libraries and tools, which makes it ideal for writing production-level software. Plus, Java garbage collection, the process by which Java programs perform automatic memory management, is invaluable for developers looking to avoid the pains and dangers of manual memory management (which is required in lower-level languages).
Critically for some clients, Java can still reach performance levels that are close to the more powerful languages currently available but without some of the development overhead. It’s also cross-platform, so a program written in Java will run on Windows, Mac or Linux, making it applicable in different areas for a variety of reasons in both large or small scale applications.
Without a doubt, Apache Spark™ has transformed how we handle big data. This open-source, distributed computation framework has a large number of applications and, alongside its core data-processing engine, it includes libraries for SQL, graph computation, machine learning and much more.
The explosion of data globally means typical data methods are no longer viable for providing the insights companies require. Because it processes data in-memory, Spark™ is much faster than its predecessor, Map Reduce, and is capable of managing petabytes of data across physical or virtual servers.
Spark™ is particularly effective for analysis of real-time streams of data. For example, Amazon uses Spark to analyse every single click you make on their site and then leverages this information to personalise their prices and recommendations. This is Spark Streaming, and you see these frameworks in practice every day across major sites. As a result, every significant player across every market is now moving towards this new type of data handling.
While the application of newer languages, such as Java and Python, have soared in recent years, C++ still plays a crucial role in modern IT.
Major operating systems such as Linux and Windows are written in C and C++, respectively. It’s used in developing modern databases such as MySQL and MongoDB, as well as in machine learning, telephone switches and embedded systems.
Crucially, C++ is extremely popular in Capital Markets, particularly in the low latency space where applications process billions of transactions daily. Direct influence on memory layout, raw byte marshalling, and compiler optimisation are features that mark this language as unique to serve the low latency space. Plus, high risks involved in migrating to applications developed in other languages means C++ is not going anywhere anytime soon.
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Stay tuned to our nearshoring blog series to learn about all of the benefits of nearshoring and some of the world’s emerging hotspots. Can’t wait that long? Download our free guide: