On Sun, Jul 31, 2016 at 11:50 PM, pooja3490 <poomazum...@gmail.com> wrote:
> Hi, > > I wanted to know that in use case where we need in-memory big data for > on-the-fly computation, does Ignite gives better performance as compared to > kdb (which is also an in-memory database)? > > As far as I understand, Ignite is used for caching database that store data > on disk or to improve performance of systems that already use spark/hadoop. > > It would be very informative if someone could share comparison of Ignite > Vs. > KDb keeping the above use case in mind. > > We don't have a comparison of Ignite to KDB, but at a high level KDB is a time-series database. It also does not seem like KDB is a distributed system either. If you are interested in time-series queries, then in Ignite it would be achieved using SQL and querying *between* timestamps using standard SQL syntax. Ignite performance should be better simply because Ignite can split a data set into multiple pieces and run the query in parallel across multiple nodes. So, if you have 10 nodes, then each node should work in parallel with D/10 data size, where D is your total data size. Given that each node has to process less data, queries should execute faster. > > > -- > View this message in context: > http://apache-ignite-developers.2346864.n4.nabble.com/Use-cases-for-Ignite-tp2132p10290.html > Sent from the Apache Ignite Developers mailing list archive at Nabble.com. >
