Hi Dmitriy, Seeing such a great excitement at the Google Cloud Platform Live event, and numbers from BigQuery demo, I'd say it's a good time to add high performance in-memory components to Hadoop Stack, and BigTop would be a natural place to start.
Perhaps you could point to a quick technology intro and differentiators? Thanks, Anatoli On Monday, March 24, 2014 11:12 PM, Roman Shaposhnik <[email protected]> wrote: Hi Dmitriy! Welcome to the Bigtop community! On Mon, Mar 24, 2014 at 10:43 PM, Konstantin Boudnik <[email protected]> wrote: >> One of the main pieces of our platform is our In-Memory Apache Hadoop >> Accelerator which aims to accelerate HDFS and Map/Reduce by bringing both, >> data and computations into memory. We do it with our GGFS - Hadoop >> compliant in-memory file system. For I/O intensive jobs GridGain GGFS >> offers performance close to 100x faster than standard HDFS. More >> information can be found here: >> http://www.gridgain.org/features/hadoop-acceleration/ >> >> We would like to have an opportunity to integrate our Apache Hadoop >> Accelerator with Apache Bigtop. Please let us know if this is possible and >> what steps are required of us. I've been actually fascinated by the in-memory analytics platforms lately. Things like Apache Spark seem to be a really good addition to the Hadoop ecosystem. Now, I understand that you've got a piece of technology that can essentially serve as a replacement for HDFS, but could you please elaborate on what other integration points do you have between GridGain and the rest of Hadoop ecosystem? That, I think, would be a much wider discussion. Thanks, Roman.
