ures, such as allowing multiple users to
>>> run commands on the same cluster and running multiple versions of Spark.
>>> Because Databricks is also the team that initially built Spark, the service
>>> is very up to date and integrated with the newest Spark features -- e.g.
>>&g
; but Databricks adds several features, such as allowing multiple users to
>>>> run commands on the same cluster and running multiple versions of Spark.
>>>> Because Databricks is also the team that initially built Spark, the
>>>> service is very up to date and
ks is based on Standalone mode, not YARN,
>> but Databricks adds several features, such as allowing multiple users to
>> run commands on the same cluster and running multiple versions of Spark.
>> Because Databricks is also the team that initially built Spark, the service
>&
ands on the same cluster and running multiple versions of Spark.
> Because Databricks is also the team that initially built Spark, the service
> is very up to date and integrated with the newest Spark features -- e.g.
> you can run previews of the next release, any data in Spark can be
>
As a user of AWS EMR (running Spark and MapReduce), I am interested in
potential benefits that I may gain from Databricks Cloud. I was wondering
if anyone has used both and done comparison / contrast between the two
services.
In general, which resource manager(s) does Databricks Cloud use for Spar
