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From Gavin Li <>
Subject Re: [PROPOSAL]Pistachio
Date Mon, 29 Jun 2015 18:27:11 GMT
Hi Roman,

I've taken a brief look at Geode. Pistachio and Geode both can support
similar in-memory consistent HA distributed storage, and the data aware
function routing idea is also similar. Here are what I think are different:

1. Pistachio actually uses a very different approach to resolve the
problem. Pistachio leverages Apache Helix to do partition management and
Apache Kafka as a WAL implementation to leverage the rich features and
great performances in those systems.
2. Pistachio supports simple plugin of different storage engines like pure
memory or different disk based local storage engines like kyoto cabinet or
Rocks DB. On our production we mainly used kyoto cabinet based SSD storage
system to optimize for read to resolve the low latency high volume read
problem in RTB applications.

Gavin Li

On Mon, Jun 22, 2015 at 8:25 PM, Gavin Li <> wrote:

> Roman,
> I think Pistachio is similar to Ignite in the sense that they both try to
> distribute the computation to storage to co-locate the data and
> computation. One difference might be Pistachio also supports other storage
> options like disk based storage to support longer term durability. Actually
> Pistachio was originally developed as a storage system of SSD disk and has
> been used on our large scale production serving system with SSD disk.
> We're not that familiar with Geode, I'll look into it and provide some
> detailed comparisons.
> Thanks,
> Gavin Li
> On Mon, Jun 22, 2015 at 8:00 PM, Roman Shaposhnik <>
> wrote:
>> On Mon, Jun 22, 2015 at 7:54 PM, Gavin Li <> wrote:
>> > The other difference is in Pistachio we can do computation based on
>> > in-memory storage with data replication. Different from the in-memory
>> > computation in Spark, the storage can be in-memory here.
>> Have you guys looked at in-memory computation layers offered by
>> Ignite and Geode? I would love to know what you think about those.
>> Thanks,
>> Roman.
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