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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 ...
RCFile has been adopted in real-world systems for big data analytics. RCFile became the default data placement structure in Facebook's production Hadoop cluster. [2] By 2010 it was the world's largest Hadoop cluster, [3] where 40 terabytes compressed data sets are added every day. [4]
Some researchers have made a functional and experimental analysis of several distributed file systems including HDFS, Ceph, Gluster, Lustre and old (1.6.x) version of MooseFS, although this document is from 2013 and a lot of information are outdated (e.g. MooseFS had no HA for Metadata Server at that time).
HBase runs on top of HDFS and is well-suited for fast read and write operations on large datasets with high throughput and low input/output latency. HBase is not a direct replacement for a classic SQL database , however Apache Phoenix project provides a SQL layer for HBase as well as JDBC driver that can be integrated with various analytics and ...
Alluxio sits between computation and storage in the big data analytics stack. It provides a data abstraction layer for computation frameworks, enabling applications to connect to numerous storage systems through a common interface. The software is published under the Apache License.
Big data analytics has been used in healthcare in providing personalized medicine and prescriptive analytics, clinical risk intervention and predictive analytics, waste and care variability reduction, automated external and internal reporting of patient data, standardized medical terms and patient registries.
SAP IQ provides federation with the Hadoop distributed file system (HDFS), a very popular framework for big data, so that enterprise users can continue to store data in Hadoop and utilize its benefits. Integration is achieved in four different ways, depending on the user's needs, through client-side federation, ETL, data, and query federation.
CarbonData: an indexed columnar data format for fast analytics on big data platform, e.g., Apache Hadoop, Apache Spark, etc; Cassandra: highly scalable second-generation distributed database; Causeway(formerly Isis): a framework for rapidly developing domain-driven apps in Java; Cayenne: Java ORM framework