Struggling With Big Data Management? Top 10 Open Source Software That Will Make Your Life Easy

“Big data is at the foundation of all the megatrends that are happening today, from social to mobile to cloud to gaming.” – Chris Lynch, Vertica Systems

Do you know how much data we are creating every day? We are creating 2.5 Exabyte of data every day, which is enough to fill 10 million blue-ray discs. If these Blu-ray discs are stacked up one over the other, it will reach the height of 4 Eiffel Towers combined. Eric Schmidt, the former CEO of Google, once pointed out to the pace at which we are creating data by saying, “There were 5 Exabyte of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.”

Managing this massive amount of data is not easy. Thankfully, there are tools that will help you in managing big data efficiently. In this article, you will learn about 10 open source tools that make big data management a breeze.

1.Apache Hadoop

Hadoop is a framework and architecture that make big data processing and storage hassle free. Apache’s Hadoop is one of the most popular data processing software but what makes it so popular is its ability to process large amounts of both structured and unstructured data and its intuitive interface. This is not all, it can also mirror chunks of data to nodes and make it accessible on local machines. Apache’s focus is on taking full advantage of Hadoop and this software clearly shows that.

2.GridGrain

If you want to analyze big data in real time, then GridGrain is for you. Compatibility with Hadoop distributed file system along with the ability to conduct quick big data analysis of real-time data makes this tool stand in a different league. Another advantage is that GridGrain is compatible with your existing dataset and its low latencies are a big bonus for data managers.

3.Contiki

Leave big data management tools and software and switch to big data management and analytics which is tailor-made for this purpose. Contiki fits the bill perfectly. It is a full-fledged operating system which is compatible with wide variety of hardware. Are you worried about the steep learning curve? Don’t worry because Contiki have you covered. The operating system has enough documentation available to even help beginners who do not know much about it use it effectively. Developers can also benefit from the extensive documentation and make mobile app development or software development easy.

4.Cassandra

Originally developed and backed by Facebook, Cassandra is an open source database management tool, which is very popular among large enterprises. Netflix, Twitter, and Reddit are among its users. The good thing about this database management software is that it is not restricted to any particular operating system and is operating system independent. This means that you can use this software irrespective of which operating system you are using.

5.Apache Storm

Don’t like Hadoop? Do you want to use any other framework for big data management and analytics? If the answer to both these question is yes, then Apache Storm is an ideal choice for you. It is an open source, areal-time computational system that assists you in process large amount of unstructured data. It’s simple and easy to use interface combined with the ability to configure it with any programming language take the hassle out of the process and make developers life a whole lot easier. Apache Storm truly shines when it comes to machine learning, real-time big data analytics, and continuous computations.

6.Lumify

Are you searching for a Hadoop alternative? If yes, then your search is over because Lumify is here. Although, it is a new entrant in the big data sphere and will not offer you the compatibility and support that you expect from Hadoop it will surely deserve consideration. It’s brilliant web-based interface let you sift through complex data and establish relationships among data sets with 2D and 3D visualizations. Add to that the ability to share workspaces in real time, view dynamic histograms and interactive geospatial views, it makes Lumify a formidable competitor of Hadoop and deserves a try.

7.RapidMiner

Previously known as YALE, the change in name has led to change in its fortunes. RapidMiner uses templates based frameworks to provide advanced analytics capabilities to its users. The biggest advantage of RapidMiner is that you don’t have to be a coding wiz to take full advantage of it as developers won’t have to write any code. It is one of the best open source data mining tools out there that also offers some very useful data processing and visualization options. Add to that the predictive analysis, statistical modeling, evaluation, and deployment features and you have a very useful open source tool in RapidMiner.

8.Solr

Solr by Apache makes transferring a large amount of data a breeze. The reliability and scalability of Solr make it an excellent tool for big data aggregation and data transfer. Searching a particular data set from a large amount of data can be a daunting challenge but with Solr, that is not the case. Solr can save a lot of time and save you from much hassle.

9.Elasticsearch

For those who prefer asecure and reliable solution with the capability to extract any data from any source, Elasticsearch is a godsend. Irrespective of where your data is and in which format it is, this tool can help you with real-time data analysis and visualization. With horizontal scalabilityoptions, easy management, and powerful search feature, users can sift through large amounts of data and extract meaningful information from it within minutes. The developer-friendly language it uses takes care of different types of data including unstructured, structured or time series data.

10.Mongo DB

Another database management application made it to our list. There are many good reasons for that. If you want to analyze big data than the traditional database software is not the right choice. You want specialized database software that is made for this purpose. Same can be said for Mongo DB which is specially designed to support huge datasets. It offers full index support, replication facility and its high accessibility and availability are its unique features. It is a non-SQL database written in C++ with document-oriented storage.

Which open source tools do you use to manage big data? Feel free to share your choice in the comments section below.

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