Hi Ashish,

Transactions are a big difference between Spark SQL and MemSQL/VoltDB, but
there are other differences as well. I'm not an expert on Volt, but another
difference between Spark SQL and MemSQL is that DataFrames do not support
indexes and MemSQL tables do. This will have implications for scanning and
query execution performance. Recently released MemSQL 4 also contains
improvements to the distributed optimizer.

For large, infrequently changing data sets, you could use the MemSQL column
store and only need a single system for storage and query (Spark does not
include storage natively, so you would need to use an external data store).
You can also use Spark in combination with MemSQL, either row store or
column store, using the MemSQL Spark Connector.

Thanks,
Conor



On Thu, May 28, 2015 at 10:36 PM, Ashish Mukherjee <
ashish.mukher...@gmail.com> wrote:

> Hi Mohit,
>
> Thanks for your reply.
>
> If my use case is purely querying read-only data (no transaction
> scenarios), at what scale is one of them a better option than the other? I
> am aware that for scale which can be supported on a single node, VoltDB is
> a better choice. However, when the scale grows to a clustered scenario,
> which is the right engine at various degrees of scale?
>
> Regards,
> Ashish
>
> On Fri, May 29, 2015 at 6:57 AM, Mohit Jaggi <mohitja...@gmail.com> wrote:
>
>> I have used VoltDB and Spark. The use cases for the two are quite
>> different. VoltDB is intended for transactions and also supports queries on
>> the same(custom to voltdb) store. Spark(SQL) is NOT suitable for
>> transactions; it is designed for querying immutable data (which may exist
>> in several different forms of stores).
>>
>> > On May 28, 2015, at 7:48 AM, Ashish Mukherjee <
>> ashish.mukher...@gmail.com> wrote:
>> >
>> > Hello,
>> >
>> > I was wondering if there is any documented comparison of SparkSQL with
>> MemSQL/VoltDB kind of in-memory SQL databases. MemSQL etc. too allow
>> queries to be run in a clustered environment. What is  the major
>> differentiation?
>> >
>> > Regards,
>> > Ashish
>>
>>
>

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