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The Hadoop distributed file system (HDFS) is a distributed, scalable, and portable file system written in Java for the Hadoop framework. Some consider it to instead be a data store due to its lack of POSIX compliance, [ 36 ] but it does provide shell commands and Java application programming interface (API) methods that are similar to other ...
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.
Its file storage capability is compatible with the Apache Hadoop Distributed File System (HDFS) API but with several design characteristics that distinguish it from HDFS. Among the most notable differences are that MapR-FS is a fully read/write filesystem with metadata for files and directories distributed across the namespace, so there is no ...
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.
Hadoop Distributed File System is a distributed file system that handles large data sets running on commodity hardware (Ishengoma, 2013). It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN.
Hadoop: Java software framework that supports data intensive distributed applications; HAWQ: advanced enterprise SQL on Hadoop analytic engine; HBase: Apache HBase software is the Hadoop database. Think of it as a distributed, scalable, big data store; Helix: a cluster management framework for partitioned and replicated distributed resources
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]
The MapR File System (MapR FS) is a clustered file system that supports both very large-scale and high-performance uses. [1] MapR FS supports a variety of interfaces including conventional read/write file access via NFS and a FUSE interface, as well as via the HDFS interface used by many systems such as Apache Hadoop and Apache Spark.