Have you considered whether you have a scan heavy or a random access heavy workload? Have you considered whether you always access / update a whole row vs only a partial row? Kudu is a column store so has some awesome performance characteristics when you are doing a lot of scanning of just a couple of columns.
I don't know the answer to your question but if your concern is performance then I would be interested in seeing comparisons from a perf perspective on certain workloads. Finally, a year ago Aerospike did quite poorly in a Jepsen test: https://aphyr.com/posts/324-jepsen-aerospike I wonder if they have addressed any of those issues. Mike On Friday, May 27, 2016, Benjamin Kim <bbuil...@gmail.com> wrote: > I am just curious. How will Kudu compare with Aerospike ( > http://www.aerospike.com)? I went to a Spark Roadshow and found out about > this piece of software. It appears to fit our use case perfectly since we > are an ad-tech company trying to leverage our user profiles data. Plus, it > already has a Spark connector and has a SQL-like client. The tables can be > accessed using Spark SQL DataFrames and, also, made into SQL tables for > direct use with Spark SQL ODBC/JDBC Thriftserver. I see from the work done > here http://gerrit.cloudera.org:8080/#/c/2992/ that the Spark integration > is well underway and, from the looks of it lately, almost complete. I would > prefer to use Kudu since we are already a Cloudera shop, and Kudu is easy > to deploy and configure using Cloudera Manager. I also hope that some of > Aerospike’s speed optimization techniques can make it into Kudu in the > future, if they have not been already thought of or included. > > Just some thoughts… > > Cheers, > Ben -- -- Mike Percy Software Engineer, Cloudera
