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5 Big Data Tools in the Cloud

For Big Data analysis, companies do not necessarily need its own cluster. There are a lot of tools in the Cloud can be used to manage, structure and analyze large amounts of data.

Big Data Tools from the Cloud can help you get started. They require no upfront investment in five- or six-digit range and have some graphical user interfaces, which allow even the less experienced user can create analysis procedures that lead to meaningful results.

Even if the data to be processed are already available online, as is the case with social media feeds to receive customer information of an online store, it is worth the analysis to start directly in the network. This is especially true when it also will take place in real-time. Five major Big Data tools that can be used as a service from the Cloud are provided below.

1. Amazon Web Services (AWS)

With Amazon Elastic MapReduce (EMR), Amazon Web Services offers a comprehensive Big Data Service on the private Cloud platform. The available there AMIs (Amazon Machine Image) already contains a bootable Linux operating system, Hadoop and other software tools that are required for operation of the cluster. The Version 4.2.0 not only supports Hadoop, but also Ganglia, Hive, Hue, Pig, Mahout and Spark.

2. Google Cloud Platform

Google deals on Big Data services extensively. In addition to the open-source solutions like Hadoop , Google also includes its self-developed products like BigQuery or DataFlow. For Hadoop, Google offers a “Cloud Launcher”, which in a few minutes, a cluster can be built for distributed Big Data analysis. According to the provider, it consists of three virtual machines (n1-standard-4) including 10 GB boot disk and three standard disks with 500 GB capacity.

3. Microsoft Azure

Microsoft also promises to its public Cloud Azure a Hadoop installation in a few minutes. Azure’s Data Lake service HDInsight can be used to manage MapReduce, pigments, Hive, HBase-, Storm- or Spark projects. According provider, HDInsight is able to handle any amount of data, scaling from terabytes to petabytes on demand. Users can access the cluster by Linux or Windows.

4. IBM Analytics

According to IBM, BigInsights on Cloud provides Hadoop-as-a-service on IBM’s SoftLayer global Cloud infrastructure. It offers the performance and security of an on-premises deployment without the cost or complexity of managing your own infrastructure. It contains other components such as Ambari, YARN, Spark, Knox, HBase and Hive. An encrypted HDFS (Hadoop Distributed File System) increases data security. When placing the Hadoop environment, users can choose among three sizes Hardware per node (Small, Medium, Large).

5. SAP HANA Cloud Platform

SAP provides its in-memory database HANA as Platform as a Service ( PaaS on). SAP HANA Cloud Platform is a scalable, secure, modular, and open-standard platform as a service. It includes comprehensive functionality designed to enable customers and partners to rapidly build Cloud-based business applications that connect to and extend the value of SAP and non-SAP enterprise software. Operated by SAP, the platform is engineered for multilevel security and certified to meet the latest industry Cloud standards. SAP HANA Cloud Platform also leverages the real-time, in-memory SAP HANA database.

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