Impala is quite different from Hive and executes SQL queries natively without translating them into the Hadoop MapReduce jobs. Queries can complete in a fraction of sec. For Impala in Cloudera, it takes around 2 mins, but for Hive, it takes 20mins, not sure is this normal? From the experiment, we conclude as follows: Impala runs faster than Hive on MR3 on short-running queries that take less than 10 seconds. Hive also supports columnar store by ORC File. Cloudera's a data warehouse player now 28 August 2018, ZDNet. For the remaining 39 queries that take longer than 10 seconds, Hive on MR3 runs about 15 percent faster than Impala on average (6944.55 seconds for Impala and 5990.754 seconds for Hive on MR3). How Impala compared faster than Hive? The above graph demonstrates that Cloudera Impala is 6 to 69 times faster than Apache Hive.To conclude, Impala does have a number of performance related advantages over Hive but it also depends upon the kind of task at hand. why impala is faster than hive impala vs hive performance impala architecture impala vs hbase impala concepts and architecture impala statestore how impala is faster than hive impala statestore is used for impala architecture diagram apache impala vs hive impala … Thanks. Cloudera says Impala is faster than Hive, which isn't saying much 13 January 2014, GigaOM. The integration between Impala and Hive gives exceptional advantages to the users to use either Impala or Hive to create tables, load data, issue queries, and so on. Though the impala is faster than hive but it is memory intensive as it performs its operation on “In Memory” , hence the Impala is not one stop solution for all the ETL operations . This one tries to explain why Impala is faster than Hive even now Hives has columnar store and Tez. So we had hive that is capable enough to process these big data queries, so what made the existence of impala we will try to find the answer for this. Hive & Pig answers queries by running Mapreduce jobs.Map reduce over heads results in high latency. A2A: This post could be quite lengthy but I will be as concise as possible. hive basically used the concept of map-reduce for processing that evenly sometimes takes time for the query to be processed. to overcome this slowness of hive queries we decided to come over with impala. if yes, why does Impala run much faster than Hive in Cloudera? Cloudera’s Impala brings Hadoop to SQL and BI 25 October 2012, ZDNet. why impala is faster than hive impala vs hive performance impala vs hive vs pig what is difference between hive and impala ? 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