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From Nicolas Paris <>
Subject Phoenix Performances & Uses Cases
Date Sat, 27 Oct 2018 11:50:43 GMT

I am benchmarking phoenix to better understand its strength and
weaknesses. My basis is to compare to postgresql for OLTP workload and
hive llap for OLAP workload. I am testing on a 10 computer cluster
instance with hive (2.1) and phoenix (4.8)  220 GO RAM/32CPU versus a
postgresql (9.6) 128GO RAM 32CPU.

Right now, my opinion is:
- when getting a subset on a large table, phoenix performs the
- when getting a subset from multiple large tables, postgres performs
  the best
- when getting a subset from a large table joining one to many small
  table, phoenix performs the best
- when ingesting high frequency data, Phoenix performs the best
- when grouping by query, hive > postgresql > phoenix
- when windowning, transforming, grouping, hive performs the best,
  phoenix the worst

Finally, my conclusion is  phoenix is not intended at all for analytics
queries such grouping, windowing, and joining large tables. It suits
well for very specific use case like maintaining a very large table with
eventually small tables to join with (such timeseries data, or binary
storage data with hbase MOB enabled).

Am I missing something ?



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