hive and compare mysql
1. different query languages: hive is hql language, mysql sql is the language;
2. The different data storage location: hive data stored on hdfs, mysql data is stored in its own system (raw device or Local FS).
3. Data Format: hive can be user-defined data formats, mysql has its own system-defined format;
4. Data Update: hive does not support data updates, you can only read, can not write, sql support data update;
5. Index: hive no index, query time by mapreduce query the data again, the cause hive query data very slow, mysql indexed;
6 Delayed: hive high delay, slow, mysql low latency.
7. Data Scale: The amount of data stored in the hive super, mysql store small amounts of data;
8. The principle underlying execution: hive bottom layer is used MapReduce, mysql is Excutor actuator.
hive and compare hbase
In common: 1 are built on top of hadoop, with hadoop as the underlying storage
Difference: 2.hive is to build a batch system in order to reduce the preparation of MapReduce jobs on Hadoop, hbase to support Hadoop defects for real-time operation.
3. The full table scan database with hive + hadoop, index access, with hbase + hadoop.
4.hive query slow, hbase is very efficient and effective than the hive.
5.hive itself does not calculate and store data, and is totally dependent on hdfs MapReduce, hive purely logical table.
6.hive borrow MapReduce Hadoop hive to complete some of the command execution, the frame is calculated using MapReduce.
7.hbase physical table is not logical table, a large memory hash table, which is stored by the search engine index, easy query operation, the column is stored.
8.hive with hdfs store files, hdfs the underlying storage is to store the file system, hbase responsible for organizing files.
