We see VoltDB as a key component in many "Big Data" scenarios as these applications often have a high-throughput transactional component and need real-time alerting or analytics functionality. Coincidentally, I'm presenting a webinar next week on the very topic. You can sign-up at http://voltdb.com/content/voltdb-big-data-applications
As for the post on highscalability.com, are there specific portions of Todd's writeup that you are interested in discussing?
Thanks for getting back to me.
> We see VoltDB as a key component in many "Big Data" scenarios
With no HDD? How can a Big Data app work without some sort
of persistent storage (bigger than RAM) - unless you're talking
about Petabytes of the stuff?
OK, fair enough, let's say that the VoltDB part is just a fraction
of what you want to analyse in real time - i.e. the part that's passing
through VoltDB/s may be reasonable.
However, what I would wonder then would be, what is your permanent
persistent storage engine? Clusters of column-oriented Vertica
machines that can answer OLAP style queries?
Re: other post.
> Let's say during a stored procedure you need to make a REST call to get a discount rate
> I've worked on we've used the stored procedure approach. It works fine until it doesn't.
> So that's why projects have learned not to trust trust the success of their project
> to how good of an application server your database can be. Instead, they separate out
> logic from data and let each scale independently. This is a more risk reduced approach.
> This is a maintenance nightmare
> number of restrictions that make VoltDB less than ideal as general purpose database.
If I want to do a query that crosses two partitions - say I'want to
join records from Europe with those in the States? Or even
just simply select from both regions at the same time?
I was thinking about this - if you have a query "optimiser" that
recognises that the queries cross partitions and, knowing that they
won't interfere with each other - the data being on different
machines ensures (how, I don't know) that they are performed
on the the same timestamp value?
I find the project very interesting - it just also strikes that
there's more to a system than speed - I mean would a user notice
a 3/4 second latency for the sake of threading &c.?