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While Hive is a SQL dialect, there are a lot of differences in structure and working of Hive in comparison to relational databases. The differences are mainly because Hive is built on top of the Hadoop ecosystem, and has to comply with the restrictions of Hadoop and MapReduce. A schema is applied to a table in traditional databases.
The term Hadoop is often used for both base modules and sub-modules and also the ecosystem, [12] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Apache Impala, Apache Flume, Apache Sqoop, Apache Oozie ...
Stanbol: Software components for semantic content management; Stratos: Platform-as-a-Service (PaaS) framework; Tajo: relational data warehousing system. It using the hadoop file system as distributed storage. Tiles: templating framework built to simplify the development of web application user interfaces.
Sahara is a component to easily and rapidly provision Hadoop clusters. Users will specify several parameters like the Hadoop version number, the cluster topology type, node flavor details (defining disk space, CPU and RAM settings), and others. After a user provides all of the parameters, Sahara deploys the cluster in a few minutes.
A 2011 McKinsey Global Institute report characterizes the main components and ecosystem of big data as follows: [52] Techniques for analyzing data, such as A/B testing, machine learning, and natural language processing; Big data technologies, like business intelligence, cloud computing, and databases
The company employed contributors to the open source software project Apache Hadoop. [5] The Hortonworks Data Platform (HDP) product, first released in June 2012, [6] included Apache Hadoop and was used for storing, processing, and analyzing large volumes of data. The platform was designed to deal with data from many sources and formats.
Diagram showing the flow of data through the processing and serving layers of lambda architecture. Example named components are shown. The speed layer processes data streams in real time and without the requirements of fix-ups or completeness.
Programmers and developers use the diagrams to formalize a roadmap for the implementation, allowing for better decision-making about task assignment or needed skill improvements. System administrators can use component diagrams to plan ahead, using the view of the logical software components and their relationships on the system. [2]