Big data has been around for years; nowadays, most of the organizations understand that if they capture all the data that streams into their businesses, they can apply open source big data analytics and get significant value from it. However, many of the businesses do not know which Big data tools to use. Here are 10 open source big data tools for you:
Hadoop provides low cost distributed computing for big data. It is one of the most important open source big data tools. Hadoop has set benchmarks of performance for other Big data tools as well.
GridGain is one of the top open source big data tools that are compatible with the Hadoop Distributed File System. This big data tool ensures faster analysis of real-time data as it has got the In-Memory Compute Grid (IMCG). It works with your existing operational data set in a transactional way with low latencies.
The open source version of this Big data analytics tool can be downloaded from github.
This open source database management and Big data tool was originally developed by Facebook. Many large organizations use Cassandra to manage huge database sets. Here are some of the examples: Netflix, Twitter, and Reddit.
This is one among the OS independent Big data tools and is now being managed by the Apache foundation.
This is one of the popular open source big data tools, known for its scalability and elasticity. The tools also help in the partitioning of Big data, and reduction in querying and processing of functions.
This is one of the powerful open source big data analytics operating system. The Operating system is compatible with a wide variety of hardware. There is a large amount of documentation available for this OS and makes it easier for developers working around big data.
KNIME is one of the powerful open source big data tools for performance management. It offers a host of features like data integration and procession. The tool is compatible with operating systems like OS X, Linux, and Windows.
This is another leading open source big data analytics tool.
The Big data tool provides faster processing of data and enables simplified predictive analysis. It also helps in applying machine learning and advanced analytics for better understanding of the business data.
A file system provides an overall structure to a big data set. This structure helps in converting a data set into simplified data, that can then be analyzed. The Hadoop distributed file system is the key data storage system for Hadoop. The tool is compatible with OS X, Linux, and Windows.
Transfer of large data sets is an important aspect of big data sets. Solr is one of the most scalable and reliable big data tools for big data file transfer and aggregation. It makes the search and navigation of large data set simple and less time-consuming.
Chukwa is the last one in this list of big data analytics tools. It is an open source data collection system for monitoring large distributed systems. It is built on top of the Hadoop Distributed File System (HDFS) and Map/Reduce framework and inherits Hadoop’s scalability and robustness. Chukwa also includes a ﬂexible and powerful toolkit for displaying, monitoring and analyzing results to make the best use of the collected data.