Hadoop is a distributed file system plus a map reduce computation layer. It's geared toward processing large datasets in parallel and is well suited to batch operations (i.e. jobs that take ~10 minutes and higher). HBase sits on top of Hadoop and uses the distributed file system (HDFS) as storage layer for a distributed column oriented database. HBase can do fast random access of individual rows (~2ms - 10ms) while scaling to enormous sizes. HBase can also act as the source or destination of a map reduce job although this would only be useful in a batch situation. Additional information and details can be found at http://hadoop.apache.org and http://hbase.apache.org. For more specific answers about suitability for a certain job, we'd need to know more about your system and what you're trying to do.
Hope that helps. On Thu, Jun 17, 2010 at 12:06 PM, blargy <[email protected]> wrote: > > Hi, > > Im new to HBase as well as Hadoop and I am trying to determine if either > will be a fit for our company. Can someone quickly describe what are the > differences between HBase and Hadoop. What are they both good at? Where do > they differ? I am basically just looking for some pretty generic replies to > see if we could benefit from using either of them. > > Thanks > -- > View this message in context: > http://old.nabble.com/Hadoop-vs-HBase-tp28916401p28916401.html > Sent from the HBase User mailing list archive at Nabble.com. > > -- Eric Sammer twitter: esammer data: www.cloudera.com
