But above solutions have its own limitations too. We cannot add more and more cache to the processor to increase performance as cache have physical limits: the bigger the cache, the slower it gets. Adding more core to the processor has its cost too. Also, that cannot scale to indefinitely. These multi-core processors can run multiple threads simultaneously and that brings concurrency to the picture. We’ll discuss it later.
So, if we cannot rely on the hardware improvements, the only way to go is more efficient software to increase the performance. But sadly, modern programming language are not much efficient.
As we discussed above, hardware manufacturers are adding more and more cores to the processors to increase the performance. All the data centers are running on those processors and we should expect increase in the number of cores in upcoming years. More to that, today’s applications using multiple micro-services for maintaining database connections, message queues and maintain caches. So, the software we develop and the programming languages should support concurrency easily and they should be scalable with increased number of cores.
But, most of the modern programming languages(like Java, Python etc.) are from the ’90s single threaded environment. Most of those programming languages supports multi-threading. But the real problem comes with concurrent execution, threading-locking, race conditions and deadlocks.Those things make it hard to create a multi-threading application on those languages.
For an example, creating new thread in Java is not memory efficient. As every thread consumes approx 1MB of the memory heap size and eventually if you start spinning thousands of threads, they will put tremendous pressure on the heap and will cause shut down due to out of memory. Also, if you want to communicate between two or more threads, it’s very difficult.
On the other hand, Go was released in 2009 when multi-core processors were already available. That’s why Go is built with keeping concurrency in mind. Go has goroutines instead of threads. They consume almost 2KB memory from the heap. So, you can spin millions of goroutines at any time.
Go runs directly on underlying hardware.
One most considerable benefit of using C, C++ over other modern higher level languages like Java/Python is their performance. Because C/C++ are compiled and not interpreted.
Processors understand binaries. Generally, when you build an application using Java or other JVM-based languages when you compile your project, it compiles the human readable code to byte-code which can be understood by JVM or other virtual machines that run on top of underlying OS. While execution, VM interprets those bytecodes and convert them to the binaries that processors can understand.
But, freeing and allocating variable in those languages is a huge pain. While most of the programming languages handle object allocation and removing using Garbage Collector or Reference Counting algorithms.
Go brings best of both the worlds. Like lower level languages like C/C++, Go is compiled language. That means performance is almost nearer to lower level languages. It also uses garbage collection to allocation and removal of the object. So, no more malloc() and free() statements!!! Cool!!!
Code written in Go is easy to maintain.
Let me tell you one thing. Go does not have crazy programming syntax like other languages have. It has very neat and clean syntax.
The designers of the Go at google had this thing in mind when they were creating the language. As google has the very large code-base and thousands of developers were working on that same code-base, code should be simple to understand for other developers and one segment of code should has minimum side effect on another segment of the code. That will make code easily maintainable and easy to modify.
Go intentionally leaves out many features of modern OOP languages.