Top 5 Open Source Big Data Tools!
Today data has more value than any other material. It is because we are living in the age of information, where data means business. As population increases, so does their data. This data can help in many things, starting from predicting markets in the future to customize products for specific sections of the population. It is not just for private institutions. Governments also rely a lot on big data.
Data is often coming through numerous sources, making the end product highly messy. If you want an analogy for that, open Google and type any keyword you want to search. Once the result page shows up, then you can have a glance over the results. Millions of links showing up on the search results page. That is pretty much how it feels when a heap of data is thrown at you. This is what big data is.
Let us now understand big data in a more formal definition.
Big Data
The term ‘Big Data’ refers to huge data-sets available in both unstructured and structured. These are so complex that they need more sophisticated processing systems than the traditional data processing application software. Also, it can infer to the process of using predictive analytics to extract value from a data set. User behavior analytics or other advanced data analysis technology can also be a source to extract the same. To learn Big Data concepts from ground up, you can check Big Data tutorials online.
Now, let us look over some of the tools to help you go through big data:
#1. Apache Hadoop
Apache Hadoop currently is the most popular distributed data processing software and for the right reasons too. It is infamous for its ease and its capabilities in the context of processing large data in both unstructured and structured formats.
#2. Lumify
Though comparatively new in the market, it is an excellent alternative to Hadoop. It is blessed with the capability to quickly go through an ample quantity of data sizes in sources and formats. Another impressive feat of its web-based interface which allows users to seek the relationships between the available data with the use of 2D and 3D graph visualizations, dynamic histograms, full text faceted search, and collaborative workspaces shared in real time.
#3. Apache Storm
Apache Storm is an open source real-time computation system. It can be used with or without Hadoop and it makes it easier to process unbounded streams of data, especially for real-time processing. It is very easy to use and can function quite well with most programming languages. This way the user can choose which language he or she would prefer to use.
#4. HPCC Systems Big Data
HPCC is a great alternative to Hadoop and is a brilliant platform for manipulating, transforming, querying and data warehousing. It is known for its excellent performance, scalability, and agility.
#5. R-Programming
One of the best features of R is that it is both a software and a language. Project is the R software whereas R programming is the programming language. Both are open source, however. To know more about R programming, you try out the R Programming online course for beginners.
If you have used any of these tools before, let us know your experience in the comments below!
