Just to add to excellent Cos's response:
- The code base for Apache Ignite has been in production usage since 2007.
It's the only in-memory system that I'm aware of that can boast over 2000
nodes in a single mission critical installation working in a fully
Some of us prefer Scala over Java :) Yet, Apache Ignite can be natively
used with either Java, Scala or Groovy.
On Mon, Apr 27, 2015 at 4:05 PM, Konstantin Boudnik <[hidden email]> wrote:
> Hi Iker and welcome!
> It's nice to have more ppl being involved into the project and bringing in
> ideas, feedback and code!
> I'd like to touch on a couple of differences between Ignite and Spark, but
> am sure other ppl will add their views as well.
> - The main different is, of course, that Ignite is in-memory computing
> system, e.g. the one that treats RAM as primary storage facility.
> others - Spark included - only use RAM for precessing.
> - Ignite's mapreduce is fully compatibly with Hadoop MR APIs which let
> everyone to simply reuse existing legacy MR code yet run it with >30x
> performance improvement.
> - Also, unlike Spark's the streaming in Ignite isn't quantified by the
> of RDD. In other words, you don't need to form an RDD first before
> processing it; you can actually do the real streaming.
> - Unlike Spark Ignite doesn't have the issue with data spil-overs to the
> (which was attempted to be addressed with Tachyon)
> - as one of the components, Ignite provides the first-class citizen
> file-system caching layer. Note, there's a Tachyon project and I have
> already addressed the differences between that and Ignite in , but
> like my post got deleted for some reason. I wonder why? ;) 
> - Ignite's uses off-heap memory to avoid GC pauses, etc. and does it
> - Ignite guarantees strong consistency
> - Ignite supports full SQL99 as one of the ways to process the data w/
> support for ACID transactions (as you have pointed out)
> - with Ignite a Java programmer shouldn't learn new ropes of Scala. And I
> will withhold my my professional opinion about the latter in order to
> this threat polite and concise ;)
> I can keep on rumbling for a long time, but you might consider reading 
> , where Nikita Ivanov - one of the founders of this project - has a good
> reflection on key differences.
>  http://bit.ly/1JvTAB6 >  https://twitter.com/c0sin/status/592825217606688768 >  http://www.infoq.com/articles/gridgain-apache-ignite >  http://www.odbms.org/blog/2015/02/interview-nikita-ivanov/ >
> Hope it helps to clarify the differences a bit.
> On Mon, Apr 27, 2015 at 05:20PM, Iker Huerga wrote:
> > Hi Ignite team,
> > My name is Iker Huerga, I'm a Software Engineer, Data Scientist and
> > entrepreneur with more than 8 years of experience in Java, I was a
> > Lucene/Solr contributor in the past, and have been using Hadoop in
> > production for more than 3 years now.
> > After being contacted by one the members of this community I got intriged
> > by the project you guys are working on. I took a look at the code and
> > documentation, and would like to say 'kudos' to all of you. It's clear
> > there is a huge amount of work behind Ignite.
> > I would like to see whether I can be a contributor to Ignite, but there's
> > been a question in the back of my mind since I started reading about
> > Ignite, what is the main difference with Apache Spark?
> > Please note that I've already read the proposal , and I get the point
> > that Ignite is a more general in-memory engine. But Spark also provide
> > streaming processing, mapreduce computations, etc. Would you say the main
> > difference is ACID trx in memory?
> > Also, what is the route map for Ignite? Is it production ready?
> > Sorry for so many questions..... in exchange of an answer I can take care
> > of https://issues.apache.org/jira/browse/IGNITE-640 if you guys want to
> > assign it to me
> > Thanks in advance!
> > Iker
> >  https://wiki.apache.org/incubator/IgniteProposal > >
> > --
> > Iker Huerga
> > http://www.ikerhuerga.com/ > > ᐧ