Gavin Clarke and Chris Mellor about AWS Storage Gateway:

Once you’ve got them by the data, of course, their hearts and minds will follow, and Amazon’s using the AWS Storage Gateway beta as a sampler for the rest of its compute cloud.

The Storage Gateway is another piece, together with S3, DynamoDB, SimpleDB, Elastic MapReduce, in Amazon’s great strategical puzzle of a complete polyglot platform.

Original title and link: Get them by the data (NoSQL database©myNoSQL)

via: http://www.theregister.co.uk/2012/01/25/amazon_cloud_enterprise_storage/

Adrian Cockcroft:

So the lesson here is that for a first step into NoSQL, we went with a hosted solution so that we didn’t have to build a team of experts to run it, and we didn’t have to decide in advance how much scale we needed. Starting again from scratch today, I would probably go with DynamoDB. It’s a low “friction” and developer friendly solution.

You can look at this in two ways: 1) a biased opinion of someone that has already betted on Amazon with the infrastructure of a multi-billion business; 2) the opinion of someone that has accumulated a ton of experience in the NoSQL space and that is successfully¹ running the infrastructure of a multi-billion business on NoSQL solutions. I’d strongly suggest you to think of it as the latter.

Original title and link: Thoughts on SimpleDB, DynamoDB and Cassandra (NoSQL database©myNoSQL)

via: http://perfcap.blogspot.com/2012/01/thoughts-on-simpledb-dynamodb-and.html

Graeme Rocher:

Grails 2.0 is the first release of Grails that truly abstracts the GORM layer so that new implementations of GORM can be used. […] The MongoDB plugin is at final release candidate stage and is based on the excellent Spring Data MongoDB project which is also available in RC form. […] Grails users can look forward to more exciting NoSQL announcements in 2012 with upcoming  future releases of GORM for Neo4j, Amazon SimpleDB and Cassandra in the works.

This is great news.

The very very big news would be a Grails version that doesn’t default anymore to using Hibernate for accessing a relational database.

Original title and link: Grails 2.0 and NoSQL (NoSQL database©myNoSQL)

via: http://blog.springsource.org/2011/12/15/grails-2-0-released/

This article highlights the benefits of connecting mobile devices to the cloud while also presenting an Amazon SimpleDB use case. Amazon SimpleDB is a highly available, flexible, and scalable non-relational data store that offloads the work of database administration. The app described here demonstrates how to store a high score list or leader board in SimpleDB. The app enables the user to view the high scores sorted by name or score, add and remove scores, and more.

What it doesn’t highlight is what happens with your application if your mobile device is disconnected.

Original title and link: Storing High Scores in Amazon SimpleDB (NoSQL database©myNoSQL)

via: http://www.amazonappstoredev.com/2011/11/h1storing-high-scores-in-amazon-simpledb-using-the-aws-sdk-for-androidh1-p-this-article-highlights-the-benefits-of-co-1.html

Todd Hoff about NoSQL and Cloud at Netflix:

You might have consistency problems if you have: multiple datastores in multiple datacenters, without distributed transactions, and with the ability to alternately execute out of each datacenter;  syncing protocols that can fail or sync stale data; distributed clients that cache data and then write old back to the central store; a NoSQL database that doesn’t have transactions between updates of multiple related key-value records; application level integrity checks; client driven optimistic locking.

Original title and link: Netflix: Run Consistency Checkers All The Time To Fixup Transactions (NoSQL databases © myNoSQL)

via: http://highscalability.com/blog/2011/4/6/netflix-run-consistency-checkers-all-the-time-to-fixup-trans.html

Nati Shalom (Gigaspaces) pulls out a couple of references from James Hamilton’s posts^[1] on Amazon SimpleDB and Google Megastore consistency model concluding:

It is interesting to see that the reality is that even Google and Amazon - which I would consider the extreme cases for big data - realized the limitation behind eventual consistency and came up with models that can deal with scaling without forcing a compromise on consistency as I also noted in one of my recent NoCAP series

But he lefts out small details like these:

Update rates within a entity group are seriously limited by:

• When there is log contention, one wins and the rest fail and must be retried
• Paxos only accepts a very limited update rate (order 10^2 updates per second)

and

Cross entity group updates are supported by:

• two-phase commit with the fragility that it brings
• queueing ans asynchronously applying the changes

Original title and link: Amazon SimpleDB, Google Megastore & CAP (NoSQL databases © myNoSQL)

via: http://natishalom.typepad.com/nati_shaloms_blog/2011/02/a-interesting-note-on-google-megastore-cap.html

Tom Borthwick:

Amazon’s SimpleDB is a NoSql datastore with a whole lot of no: no sql, no datatypes (except utf-8 strings), no transactions, no joins, no indexes, no schema, no administration, and no cost for minimal usage. But when you google it, you find Amazon’s docs, a lot of bold predictions about it from 2007 and 2008… and not much else. SimpleDB seems like an interesting solution in search of a problem, but its ease of use and lack of administration effort make it worth at least checking out.

There are a few yes in the SimpleDB offering, but firstly you need to get by the nos.

Original title and link: Amazon SimpleDB: An Intro (NoSQL databases © myNoSQL)

via: http://www.copperykeenclaws.com/introduction-to-amazon%E2%80%99s-simpledb/

Sid Anand, Netflix cloud engineer, shares a set of tips for optimizing access to SimpleDB based on his extensive experience using it:

I’ve been a heavy-user of SimpleDB since January 2009, storing, writing, and reading billions of items. Based on my experience, I’ve compiled a list of best practices and conventions to simplify working with SimpleDB.

His article talks about handling numerical and time data, UUIDs/GUIDs, composite value attributes, batched PUTs and a couple more tricks.

Update: Now the original post got split in three parts: ☞ part 2, covering tips on case sensitiveness, sharding, non-indexed queries, eventual consistency and batched PUTs, and ☞ part 3 sharing tips on attribute value length, default query limit,

via: http://practicalcloudcomputing.com/post/712653349/simpledb-essentials-for-high-performance-users