引用文档：
The Hadoop Distributed File System: Architecture and Design
http://hadoop.apache.org/core/docs/r0.16.4/hdfs_design.html
HDFS Under the Hood Presentation 1
http://assets.en.oreilly.com/1/event/12/HDFS%20Under%20the%20Hood%20Presentation%201.pdf
Kosmos File System (KFS) is a New High End Google File System Option
http://highscalability.com/kosmos-file-system-kfs-new-high-end-google-file-system-option
Hadoop HBase Performance Evaluation Introduction
http://www.cs.duke.edu/~kcd/hadoop/kcd-hadoop-report.pdf
Hbase/HbaseArchitecture
http://wiki.apache.org/hadoop/Hbase/HbaseArchitecture
Hbase/DataModel
http://wiki.apache.org/hadoop/Hbase/DataModel
Understanding HBase and BigTable
http://jimbojw.com/wiki/index.php?title=Understanding_Hbase_and_BigTable
The End of an Architectural Era (It’s Time for a Complete Rewrite)
http://www.vldb.org/conf/2007/papers/industrial/p1150-stonebraker.pdf
HBase Leads Discuss Hadoop, BigTable and Distributed Databases
http://www.infoq.com/news/2008/04/hbase-interview
Validating the Real-time Performance of Hbase
http://wiki.apache.org/hadoop/Hbase/HbaseRTDS
Hadoop Summit and Data-Intensive Computing Symposium Videos and Slides
http://research.yahoo.com/node/2104
Google Datastore and the shift from a RDBMS
http://groovie.org/2008/04/13/google-datastore-and-the-shift-from-a-rdbms
One Size Fits All? – Part 2: Benchmarking Results
http://nms.csail.mit.edu/~stavros/pubs/osfa.pdf
Bigtable: A Distributed Storage System for Structured Data
http://labs.google.com/papers/bigtable-osdi06.pdf
Hypertable领导者:Hadoop和分布式数据库
http://www.builder.com.cn/2008/0506/847804.shtml
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HBase is the Hadoop database. Its an open-source, distributed, column-oriented store modeled after the Google paper, Bigtable: A Distributed Storeage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Hadoop.
HBase’s goal is the hosting of very large tables — billions of rows X millions of columns — atop clusters of commodity hardward. Try it if your plans for a data store run to big.
The Hadoop Distributed File System: Architecture and Design
http://hadoop.apache.org/core/docs/r0.16.4/hdfs_design.html
HDFS Under the Hood Presentation 1
http://assets.en.oreilly.com/1/event/12/HDFS%20Under%20the%20Hood%20Presentation%201.pdf
Kosmos File System (KFS) is a New High End Google File System Option
http://highscalability.com/kosmos-file-system-kfs-new-high-end-google-file-system-option
Hadoop HBase Performance Evaluation Introduction
http://www.cs.duke.edu/~kcd/hadoop/kcd-hadoop-report.pdf
Hbase/HbaseArchitecture
http://wiki.apache.org/hadoop/Hbase/HbaseArchitecture
Hbase/DataModel
http://wiki.apache.org/hadoop/Hbase/DataModel
Understanding HBase and BigTable
http://jimbojw.com/wiki/index.php?title=Understanding_Hbase_and_BigTable
The End of an Architectural Era (It’s Time for a Complete Rewrite)
http://www.vldb.org/conf/2007/papers/industrial/p1150-stonebraker.pdf
HBase Leads Discuss Hadoop, BigTable and Distributed Databases
http://www.infoq.com/news/2008/04/hbase-interview
Validating the Real-time Performance of Hbase
http://wiki.apache.org/hadoop/Hbase/HbaseRTDS
Hadoop Summit and Data-Intensive Computing Symposium Videos and Slides
http://research.yahoo.com/node/2104
Google Datastore and the shift from a RDBMS
http://groovie.org/2008/04/13/google-datastore-and-the-shift-from-a-rdbms
One Size Fits All? – Part 2: Benchmarking Results
http://nms.csail.mit.edu/~stavros/pubs/osfa.pdf
Bigtable: A Distributed Storage System for Structured Data
http://labs.google.com/papers/bigtable-osdi06.pdf
Hypertable领导者:Hadoop和分布式数据库
http://www.builder.com.cn/2008/0506/847804.shtml
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What Is Hadoop?
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing, including:
- Hadoop Core, our flagship sub-project, provides a distributed filesystem (HDFS) and support for the MapReduce distributed computing metaphor.
- HBase builds on Hadoop Core to provide a scalable, distributed database.
HBase’s goal is the hosting of very large tables — billions of rows X millions of columns — atop clusters of commodity hardward. Try it if your plans for a data store run to big.