Best cloud service to deploy Neo4j instances?

[Javier de la Rosa]

Hi all,

I am in the moment of a project [1] in which we have to abandon our
inner and demo infrastructure and adopt a cloud-based service, what is
a very new field to me.
As far as I am suscribed on this list, I read that Amazon EBS is not a
good option, because ephimeral drive is better. But at the same time,
many users have their instances in EC2 with EBS. What about S3? On the
other hand we have Heroku, Azure or RackSpace

Very likely we will use the REST API to connect with our Neo4j
instances, and there will be as many instances as users paying for
that service, so it should be possible to launch or create new
instances, like AMI, under request through an API with the cloud
service.

What do you think is better?



[1] http://sylvadb.com/

[Andreas Kollegger]

The critical consideration for running a database on any cloud infrastructure is optimizing disk I/O. As with any deployment: establish an appropriate performance benchmark, then test different combinations of hosts, storage and networks. Assume failure -- that everything will go up in flames at the worst possible time -- and plan accordingly. 

-Andreas

[Romiko Derbynew]

Im not sure Disk IO is that important, if the graph is less that available memory then Memory is more important as Neo4j puts the entire graph in memory when possible. Well that is why it is important you change the heap size settings from its default. I would go with Memory then Disk.

Romiko

[Michael Hunger]

Agreed, the only drawback is as a transactional database neo4j flushes writes to the tx-log on tx-commit.
So at least that has to be fast.

The other aspect is initial loading/random hits on cold caches.

Michael

Am 11.09.2012 um 03:17 schrieb Romiko Derbynew:

> Im not sure Disk IO is that important, if the graph is less that available memory then Memory is more important as Neo4j puts the entire graph in memory when possible. Well that is why it is important you change the heap size settings from its default. I would go with Memory then Disk.
>
> Romiko
>

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>
>

[Javier de la Rosa]

Thank guys. I think I will try Amazon first, properly setting up Neo4j.

Regards.

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>
>



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Javier de la Rosa
http://versae.es

[Pablo Pareja]

Hi Javier,

I use AWS with EBS volumes for the DB and so far I'm pretty happy with the results.

Cheers,

Pablo

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[Javier de la Rosa]

On Wed, Sep 12, 2012 at 3:31 AM, Pablo Pareja <ppa...@era7.com> wrote:
> I use AWS with EBS volumes for the DB and so far I'm pretty happy with the
> results.

Hi, Pablo, if it is not much asking, what setup do you have and what
numbers, in terms of nodes, relationships and properties, are your
instances managing?

Thanks!

[Pablo Pareja]

Hey,

Actually it depends a lot on the case, ranging from projects with ~1 million nodes & relationships using m1.medium/m1.large instances to DBs with ~ 1 billion nodes & rels where I could need different types of instances depending on the scenario (from m1.large to m2.2xlarge instance types).

Anyways the Disk IO never was a real limitation for me, way before that my DB was always struggling with my beloved so-called supernodes.... :P

Cheers,

Pablo

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[Duane Nickull]

From my personal relationships with both Peter N (Neo4J) and James W. (Heroku), I would have to say that the answer to your question is that Heroku is probably the best cloud provider for Neo4J.  I must also qualify this statement that this is solely based on my personal relationships with people who I deem of "ultra high intelligence" and believe that due to the long standing history between the two companies, they have optimized the models for how they offer Neo4J.

Of course you can host Neo4J on any cloud provider, but Heroku and Neo Technologies have worked together for a substantial time period to work out many kinks in the systems. Not only that, but the way they provide services to customers is highly aligned in a linear fashion in terms of monetary billing WRT functional capacity for dollars spent.

YAMMV but in general, I would invite this combination to be evaluated in the context of the subject header.

Duane Nickull

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t.  @duanechaos

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