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With the rise in the volume of Big Data and tremendous growth in cloud computing, the cutting edge Big Data Analytics Tools have become the key to achieve a meaningful analysis of data. In this article, we shall discuss the top Big Data Analytics tools and their key features.
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Apache Storm: Apache Storm is an open-source and free big data computation system. Apache Storm also an Apache product with a real-time framework for data stream processing for the supports any programming language. It offers distributed real-time, fault-tolerant processing system. With real-time computation capabilities. Storm scheduler manages workload with multiple nodes with reference to topology configuration and works well with The Hadoop Distributed File System (HDFS).
Talend: Talend is a big data tool that simplifies and automates big data integration. Its graphical wizard generates native code. It also allows big data integration, master data management and checks data quality.
Apache Spark: Spark is also a very popular and open-source big data Software tool. Spark has over 80 high-level operators for making easy build parallel apps. It is used at a wide range of organizations to process large datasets.
Splice Machine: It is a big data analytics tool. Their architecture is portable across public clouds such as AWS, Azure, and Google.
Plotly: Plotly is an analytics tool that lets users create charts and dashboards to share online.
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Azure HDInsight: It is a Spark and Hadoop service in the cloud. It provides big data cloud offerings in two categories, Standard and Premium. It provides an enterprise-scale cluster for the organization to run their big data workloads. You can get a better understanding with the Azure Data Engineering certification.
R: R is a programming language and free software and It’s Compute statistical and graphics. The R language is popular between statisticians and data miners for developing statistical software and data analysis. R Language provides a Large Number of statistical tests.
Skytree: Skytree is a Big data tool that empowers data scientists to build more accurate models faster. It offers accurate predictive machine learning models that are easy to use.
Lumify: Lumify is considered a Visualization platform, big data fusion and Analysis tool. It helps users to discover connections and explore relationships in their data via a suite of analytic options.
Hadoop: The long-standing champion in the field of Big Data processing, well-known for its capabilities for huge-scale data processing. It has low hardware requirement due to open-source Big Data framework can run on-prem or in the cloud. The main Hadoop benefits and features are as follows:
It is designed to scale up from Apache Hadoop is a software framework employed for clustered file system and handling of big data. It processes datasets of big data utilizing the MapReduce programming model. Hadoop is an open-source framework that is written in Java and it provides cross-platform support. No doubt, this is the topmost big data tool. Over half of the Fortune 50 companies use Hadoop. Some of the Big names include Amazon Web services, Hortonworks, IBM, Intel, Microsoft, Facebook, etc. single servers to thousands of machines. You can get a better understanding with the Data Engineering Course in India.
Qubole: Qubole data service is an independent and all-inclusive big data platform that manages, learns and optimizes on its own from your usage. This lets the data team concentrate on business outcomes instead of managing the platform. Out of the many, few famous names that use Qubole include Warner music group, Adobe, and Gannett. The closest competitor to Qubole is Revulytics.
With this, we come to an end of this article. I hope I have thrown some light on to your knowledge on Big Data tools and Technologies.
Now that you have understood Big data Analytics tools and their Key Features, check out the Big Data Course by Edureka, a trusted online learning company with a network of more than 250,000 satisfied learners spread across the globe.
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