Best Big Data Analytics Tools in 2019

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Big Data Analytics software is widely used in providing meaningful analysis of a large set of data. This software helps in finding current market trends, customer preferences, and other information.

Here are the top Big Data Analytics Tools with key feature and download links

1) Microsoft HDInsight:

Azure HDInsight 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.

Features:

  • Reliable analytics with an industry-leading SLA
  • It offers enterprise-grade security and monitoring
  • Protect data assets and extend on-premises security and governance controls to the cloud
  • High-productivity platform for developers and scientists
  • Integration with leading productivity applications
  • Deploy Hadoop in the cloud without purchasing new hardware or paying other up-front costs

2) Skytree:

Skytree is a big data analytics tool that empowers data scientists to build more accurate models faster. It offers accurate predictive machine learning models that are easy to use.

Features:

  • Highly Scalable Algorithms
  • Artificial Intelligence for Data Scientists
  • It allows data scientists to visualize and understand the logic behind ML decisions
  • Skytree via the easy-to-adopt GUI or programmatically in Java
  • Model Interpretability
  • It is designed to solve robust predictive problems with data preparation capabilities
  • Programmatic and GUI Access

3) 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.

Features:

  • Accelerate time to value for big data projects
  • Simplify ETL & ELT for big data
  • Talend Big Data Platform simplifies using MapReduce and Spark by generating native code
  • Smarter data quality with machine learning and natural language processing
  • Agile DevOps to speed up big data projects
  • Streamline all the DevOps processes

4) Splice Machine:

Splice Machine is a big data analytic tool. Their architecture is portable across public clouds such as AWS, Azure, and Google.

Features:

  • It can dynamically scale from a few to thousands of nodes to enable applications at every scale
  • The Splice Machine optimizer automatically evaluates every query to the distributed HBase regions
  • Reduce management, deploy faster, and reduce risk
  • Consume fast streaming data, develop, test and deploy machine learning models

5) Spark:

Apache Spark is a powerful open source big data analytics tool. It offers over 80 high-level operators that make it easy to build parallel apps. It is used at a wide range of organizations to process large datasets.

Features:

  • It helps to run an application in Hadoop cluster, up to 100 times faster in memory, and ten times faster on disk
  • It offers lighting Fast Processing
  • Support for Sophisticated Analytics
  • Ability to Integrate with Hadoop and Existing Hadoop Data
  • It provides built-in APIs in Java, Scala, or Python

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