Difference between Hive and HBase

integration of hive and hbase
Hive HBase
Hive is query engine HBase is a data storage particularly for
unstructured data.
Apache Hive is mainly used for
batch processing i.e. OLAP
HBase is extensively used for transactional
processing wherein the response time of the query
is not highly interactive i.e. OLTP.
Operations in Hive are
used to transformed into mapreduce jobs.
Operations in HBase are run
in real-time on the database
For big data applications that require complex
and fine grained processing, Hadoop MapReduce
is the best choice.
HBase should be used when Data model
schema is sparse.
It used for data warehousing requirements
the programmers do not
write complex mapreduce code.
HBase is an ideal big data solution if the
application requires random read or random
write operations or both.
Hive does not currently
support update statements.
HBase queries are written in a custom language
that needs to be learned.
Hive does not provide interactive
querying it only runs batch processes on Hadoop.
Apache HBase is a NoSQL key/value store which
runs on top of HDFS.
Hive has some limitations
of high latency
HBase does not have analytical capabilities
Hive is to analytical queries. HBase is to real-time querying
Hive used for analytical querying of
data collected over a period of time.Hive
should not be used for real-time querying.
HBase is perfect for real-time example
Facebook use for messaging and real-time analytics.
They may even be using it to count Facebook likes.

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