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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 ...
Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format. [3] It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet.
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.
Apache Kudu is a free and open source column-oriented data store of the Apache Hadoop ecosystem. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides completeness to Hadoop's storage layer to enable fast analytics on fast data.
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 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.