Thanks so much for the detailed response Cos, was really helpful! As far as contributing is concerned, how about assigning https://issues.apache.org/jira/browse/IGNITE-640 to me?
Best Iker ᐧ 2015-04-27 19:05 GMT-04:00 Konstantin Boudnik <[email protected]>: > Hi Iker and welcome! > > It's nice to have more ppl being involved into the project and bringing in > new > ideas, feedback and code! > > I'd like to touch on a couple of differences between Ignite and Spark, but > I > 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. > Where's > 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 > size > 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 > disk > (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 [1], but > looks > like my post got deleted for some reason. I wonder why? ;) [2] > > - Ignite's uses off-heap memory to avoid GC pauses, etc. and does it > highly > efficiently. > > - Ignite guarantees strong consistency > > - Ignite supports full SQL99 as one of the ways to process the data w/ > full > 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 > keep > this threat polite and concise ;) > > I can keep on rumbling for a long time, but you might consider reading [3] > and > [4], where Nikita Ivanov - one of the founders of this project - has a good > reflection on key differences. > > [1] http://bit.ly/1JvTAB6 > [2] https://twitter.com/c0sin/status/592825217606688768 > [3] http://www.infoq.com/articles/gridgain-apache-ignite > [4] http://www.odbms.org/blog/2015/02/interview-nikita-ivanov/ > > Hope it helps to clarify the differences a bit. > Cos > > 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 > that > > 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 [1], 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 > > > > > > [1] https://wiki.apache.org/incubator/IgniteProposal > > > > -- > > Iker Huerga > > http://www.ikerhuerga.com/ > > ᐧ > -- Iker Huerga http://www.ikerhuerga.com/
