Depends really what you want to do. Hive is more for queries involving a lot of data, whereby hbase+Phoenix is more for oltp scenarios or sensor ingestion.
I think the reason is that hive has been the entry point for many engines and formats. Additionally there is a lot of tuning capabilities from hardware over software to make it fast. Thus, other software always had it a little bit difficult. > On 19 Apr 2016, at 00:34, Mich Talebzadeh <mich.talebza...@gmail.com> wrote: > > Hi, > > I notice that Impala is rarely mentioned these days. I may be missing > something. However, I gather it is coming to end now as I don't recall many > use cases for it (or customers asking for it). In contrast, Hive has hold its > ground with the new addition of Spark and Tez as execution engines, support > for ACID and ORC and new stuff in Hive 2. In addition provided a good choice > for its metastore it scales well. > > If Hive had the ability (organic) to have local variable and stored procedure > support then it would be top notch Data Warehouse. Given its metastore, I > don't see any technical reason why it cannot support these constructs. > > I was recently asked to comment on migration from commercial DWs to Big Data > (primarily for TCO reason) and really could not recall any better candidate > than Hive. Is HBase a viable alternative? Obviously whatever one decides > there is still HDFS, a good engine for Hive (sounds like many prefer TEZ > although I am a Spark fan) and the ubiquitous YARN. > > Let me know your thoughts. > > > Dr Mich Talebzadeh > > LinkedIn > https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > > http://talebzadehmich.wordpress.com >
