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Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.
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Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
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Apache Pig [1] is a high-level platform for creating programs that run on Apache Hadoop. The language for this platform is called Pig Latin. [1] Pig can execute its Hadoop jobs in MapReduce, Apache Tez, or Apache Spark. [2]
Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.
Sqoop got the name from "SQL-to-Hadoop". [4] Sqoop became a top-level Apache project in March 2012. [5] Informatica provides a Sqoop-based connector from version 10.1. Pentaho provides open-source Sqoop based connector steps, Sqoop Import [6] and Sqoop Export, [7] in their ETL suite Pentaho Data Integration since version 4.5 of the software. [8]
Jaql (pronounced "jackal") is a functional data processing and query language most commonly used for JSON query processing on big data.. It started as an open source project at Google [1] but the latest release was on 2010-07-12.