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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.
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 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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Avro is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java.It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop.
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]