The year 2019 was momentous in many ways. We saw the release of many new versions of the operating systems that had the power to transform the world radically. While we also saw the rise and fall of many programming languages. One was the most noticeable things of the year was Python rising as the most widely used programming language, beating JAVA and others in the race. Even though today there are more than 8 million Python developers in the world, it doesn’t mean that the language is the first choice for everything.
While machine learning and data analytics might find their home in Python, there are other niches for which the highly anticipated programming language isn’t that suitable. One such field is that of Einstein Analytics.
What is Einstein Analytics?
Einstein Analytics is an advanced analytics solution that lets you explore all of your data quickly using Salesforce. It is powered by Artificial Intelligence and helps businesses and individuals accomplish plenty of things. For the starters, Einstein Analytics can be used to manage datasets, customize dashboard etc. It addresses any query data with Salesforce Analytics Query Language or SAQL. The beauty of Einstein Analytics is that it accomplishes these and other many things programmatically.
Einstein Analytics is fundamentally designed for businesses. It offers a range of pre-built applications for the sales, service and marketing department seamlessly. These applications do not just facilitate more effortless functioning of the various departments but also helps them analyze and break processes into their nuances, based on data. In other words, gives a user the flexibility to build their own customized and intelligent analytics application, utilize APIs and software development kits to enhance any existing analytics app etc. Apart from these, Einstein Analytics also aids businesses to connect to outside data sources, so that their entire data can rest in one place.
Why Python doesn’t Fit?
By now, anyone who has a hint of Python must be able to realize that hiring python developers India helps achieve all of this. Or moreover, it might be the quintessential implementation tool being used at Salesforce. However, this is far from reality. While Python is indeed a high-level language that helps accomplish mundane tasks with ease, it’s usability in an enterprise is still a question. Even though popular organizations around the world use the world’s most popular programming language, it doesn’t guarantee its effectiveness at the enterprise level.
Developers at Netflix love Python. They use it across every part of the vast online streaming infrastructure. After all, Python is flexible, platform-independent and does make large blocks of code seem easily understandable to a developer. In spite of the multitudinous benefits that Python offers, Salesforce doesn’t find it quite an optimal solution for working with Einstein Analytics. Upon critical analysis of the pros and cons of the language, engineers at Salesforce determined that it may not be the best idea to rely or fundamentally base Einstein Analytics on Python entirely. Instead, they are harnessing the power of Google’s Go for the job.
Google’s Go to the Rescue
Also known as the Golang, Google’s Go is often seeing as being the top choice of development at enterprises. Ever since its release in 2009 by experts at Google, it has been one of the most competitive and scalable languages designed with a far sight in view. At some levels, Google is giving a fierce battle to JAVA, which the world knows as the most popular enterprise development programming language. Although Golang developed out of obscurity, it has found quite the traction in the world, especially among developers for various development tasks.
Statistics suggest that Google’s Go has a significant market share among websites with higher traffic. It is also the 13th most popular programming language and stands as number five on Stack Overflow’s list of the ‘Most Dreaded, Loved and Wanted’ programming languages.
The reason why Salesforce finds Go as a better language for Einstein Analytics has many purposes. The cloud-based software company recently spent a considerable amount of $15.7 billion on the famous analytics company Tableau to empower its Analytics Solution, that we know as Einstein Analytics. Salesforce finds analytics as to the future of the world. Be it business, healthcare or any other walk of life. Analytics is the key to understanding the customer, growing a business and innovating new products.
But, before Salesforce launched Einstein Analytics, it completely overhauled its backend and built on Golang. According to the principal architect at Salesforce, Guillaume Le Stum, Einstein Analytics was initially developed to have the best of both worlds. On the one hand, the analytics product utilized the programming language C to create a query engine and dataset tools. This was meant to increase performance. On the other hand, Einstein Analytics used a Python wrapper that provided functionalities like parsing queues, REST API server etc.
The Ultimate Shift from Python to Golang
However, days before the release of Einstein Analytics, Salesforce shifted from Python to Golang. Although Python is the first choice for writing high-level applications, it doesn’t mean that one can expect a high performance at an enterprise level. During its testing phase, Einstein Analytics started showing signs of a slowdown. This was because any new query that wasn’t in-built in the core would directly load onto the Python wrapper, thus, becoming sluggish.
Python’s failure to do multi-threading was the main reason behind the bad performance of the analytics platform. It uses lose typing, which might be great for building small-scale applications but isn’t feasible for an enterprise-level application.
However, one of the main reasons that Salesforce started using Golang was because of its inbuild set of tools, quick compile times and deploys, easy troubleshooting, among others. One of the best parts of using Go for Einstein Analytics was that it increased the readability of the code and its cross-platform features make it easy to port.
Python might be the quintessential language one needs to write super elegant comprehensions that are mathematical. However, if Python code isn’t written explicitly, it would come at the cost of readability. With Goland now in the picture, it was convenient for Salesforce to develop an analytics platform without worrying about slowdowns during multi-threading or readability issues for their developers.