The difference between hive and relational database

Hive versus relational databases

hive is so similar to relational databases that there is always an illusion in hive learning that hive is a database, not a database. Hive is the client side of Hadoop, with HDFS at the bottom, and the execution engine is MapReduce, which is executed on Hadoop and, in other words, a layer of Hadoop’s client package.

1. Data update

  • hive read more write less
  • mysql usually needs to modify

2. Data delay

  • mysql usually executes in seconds
  • hive for a longer time:
    • hive query, there is no index, need to scan the whole table, so the delay is high
    • mapreduce when the hive is executed, there will be a shuffle, shuffle to drop the disk, the delay is high

3. Data size

  • hive data scale is large
    • hive is stored in HDFS and built on clusters. You can add machine vertical expansion
  • mysql has storage bottlenecks
    Mysql store on disk

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