Top Programming Languages For Big Data Framework Development

Big data is essentially a massive collection of structured as well as unstructured data. Whereas data science refers to the methods, processes, and more used to glean insights from data, be it in a structured form. As you can see, both are inherently different concepts, and yet they are often used interchangeably. This confusion can perhaps be chalked up to the fact that both Data Science and Big Data bring forth the potential to glean immeasurable value from data.

However, let’s get to the point — as these two fields continue to gain momentum, people will start to wonder precisely which programming languages are suited for such pursuits. Coding is one of the primary components when it comes to using it appropriately for these innovative tools that the evolution of technology has presented us with. Moreover, if you wish to master such domains, it is also essential to be well-versed with the programming language. In this article, we’ll take a look at the leading programming language options for developing big data frameworks.

  1. R: An open-source coding language, R also delivers a software ecosystem for graphics as well as statistical computing. Because R comes equipped with a variety of mathematical models, it fares as a highly preferred option among analysts as the coding language for their app. It also gets a variety of packages that are highly conducive for big data; this includes significant memory, fast file access, and more.
  2. Python: Yet another open-source programming language on the lust, Python is undoubtedly one of the best options in the market for building big data frameworks. In addition to the fact that it is quite simple to use and is supported by a massive community, it also gets a wide array of libraries that make it easier for developers to pick up pace through the programming process. Also, let’s not forget Pydoop; a Python interface for Hadoop, it allows developers to execute MapReduce programming by means of an authentic Python client for Hadoop pipes.
  3. Java: Java’s popularity among developers is right up there with Python. Running on Java Virtual Machine, this one brings with it the ability to consolidate data science tactics within an existing code database. Moreover, since it is the language that Hadoop is based on, it is automatically rendered crucial for any endeavor related to big data. Oh, and an expert company providing Java web application development services will also leverage Java Data Mining Package, i.e., a library for big data analytics and machine learning that empowers developers with access to not only sources of data, but also visualization modules and machine learning algorithms among other things.

Big data is an admittedly new field in the larger scheme of things, and yet, it continues to grow and evolve at a mind-boggling pace. So the easiest way to keep up with it would be to ensure that you find a robust programming language to assist you through the process of keeping pace as well as through the development of big data frameworks, and more.