Best Big Data Software for Apache HBase

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

Amazon EMR is the market-leading cloud big data platform. It processes large amounts of data with open source tools like Apache Spark, Apache Hive and Apache HBase. EMR allows you to run petabyte-scale analysis at a fraction of the cost of traditional on premises solutions. It is also 3x faster than standard Apache Spark. You can spin up and down clusters for short-running jobs and only pay per second for the instances. You can also create highly available clusters that scale automatically to meet the demand for long-running workloads. You can also run EMR clusters from AWS Outposts if you have on-premises open source tools like Apache Spark or Apache Hive.

Run popular open-source frameworks--including Apache Hadoop, Spark, Hive, Kafka, and more--using Azure HDInsight, a customizable, enterprise-grade service for open-source analytics. You can process huge amounts of data quickly and enjoy all the benefits of the large open-source project community with the global scale Azure. You can easily migrate your big data workloads to the cloud. Open-source projects, clusters and other software are easy to set up and manage quickly. Big data clusters can reduce costs by using autoscaling and pricing levels that allow you only to use what you use. Data protection is assured by enterprise-grade security and industry-leading compliance, with over 30 certifications. Optimized components for open source technologies like Hadoop and Spark keep your up-to-date.