This tutorial is meant for the .NET developers to get started with Amazon DynamoDB. I will show you how to create a Table and perform CRUD operations on it. Amazon DynamoDB provides a low-level API and an Object Persistence API for the .NET developers. In this tutorial, we will see how to use the Object Persistence API to talk to Amazon DynamoDB. We will model a component that represents a DVD Library with capabilities to add, modify, query and delete individual DVDs.

Looks like a lot of code just to demo some CRUD operations.

Original title and link: Step-by-Step Guide to Amazon DynamoDB for .NET Developers (NoSQL database©myNoSQL)

via: http://cloudstory.in/2012/02/step-by-step-guide-to-amazon-dynamodb-for-net-developers/

An ArsTechnica, not very technical, overview of the storage engines developed and used by Google (Google File System, BigTable), Amazon (Dynamo), Microsoft (Azure DFS), plus the Hadoop Distributed File System (HDFS).

Original title and link: How Web giants store big data (NoSQL database©myNoSQL)

via: http://arstechnica.com/business/news/2012/01/the-big-disk-drive-in-the-sky-how-the-giants-of-the-web-store-big-data.ars/1

While the authoritative storage is Amazon RDS, 99designs is using Redis, MongoDB, and Memcached for transient data:

We log errors and statistics to capped collections in MongoDB, providing us with more insight into our system’s performance. Redis captures per-user information about which features are enabled at any given time; it supports our development stragegy around dark launches, soft launches and incremental feature rollouts.

It’s also worth noting the nice things they say about using Amazon RDS:

An RDS instance configured to use multiple availability zones provides master-master replication, providing crucial redundancy for our DB layer. This feature has already saved our bacon multiple times: the fail over has been smooth enough that by the time we realised anything was wrong, another master was correctly serving requests. Its rolling backups provide a means of disaster recovery. We load-balance reads across multiple slaves as a means of maintaining performance as the load on our database increases.

Original title and link: 99designs: Powered by Amazon RDS, Redis, MongoDB, and Memcached (NoSQL database©myNoSQL)

via: http://99designs.com/tech-blog/blog/2012/01/30/infrastructure-at-99designs/

Billy Bosworth¹:

Personally, I have never believed that other post-relational (aka NoSQL/Hadoop) database companies were our primary competition.  The brute fact of the matter is that if you put us all together, we are still not statistically relevant compared to the overall DBMS market.

I had only one real personal fear coming into this market: That I would sink a big portion of my life into something that would never take hold in the mainstream. I suspect that would be a truly awful ending for all of us in this space. But thanks to companies like Amazon and Oracle, that feels highly unlikely now, and that is a great thing.

Just to play the devil advocate for a second: Oracle won’t lose much in the NoSQL market if things don’t work out well and Amazon’s DynamoDB is part of a larger plan. But for all the NoSQL database companies it is an all-or-nothing game².

Original title and link: DataStax’s CEO thoughts on the NoSQL Market and Competition (NoSQL database©myNoSQL)

via: http://www.datastax.com/2012/01/my-thoughts-on-amazons-dynamodb

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/

Adam Gray^[1]:

In this article, I’ll demonstrate how EMR can be used to efficiently export DynamoDB tables to S3, import S3 data into DynamoDB, and perform sophisticated queries across tables stored in both DynamoDB and other storage services such as S3.

If you put together Amazon S3, Amazon DynamoDB, Amazon RDS, and Amazon Elastic MapReduce, you have a complete polyglot persistence solution in the cloud^[2].

Original title and link: Using Amazon Elastic MapReduce With DynamoDB: NoSQL Tutorials (NoSQL database©myNoSQL)

via: http://aws.typepad.com/aws/2012/01/aws-howto-using-amazon-elastic-mapreduce-with-dynamodb.html

Tarsnap is a service offering secure online backups. Colin Percival details the costs Tarsnap would have for using Amazon DynamoDB:

For each TB of data stored, this gives me 30,000,000 blocks requiring 60,000,000 key-value pairs; these occupy 2.31 GB, but for DynamoDB pricing purposes, they count as 8.31 GB, or $8.31 per month. That’s about 2.7% of Tarsnap’s gross revenues (30 cents per GB per month); significant, but manageable. However, each of those 30,000,000 blocks need to go through log cleaning every 14 days, a process which requires a read (to check that the block hasn’t been marked as deleted) and a write (to update the map to point at the new location in S3). That’s an average rate of 25 reads and 25 writes per second, so I’d need to reserve 50 reads and 50 writes per second of DynamoDB capacity. The reads cost $0.01 per hour while the writes cost $0.05 per hour, for a total cost of $0.06 per hour — or $44 per month. That’s 14.6% of Tarsnap’s gross revenues; together with the storage cost, DynamoDB would eat up 17.3% of Tarsnap’s revenue — slightly over $0.05 from every $0.30/GB I take in.

To put it differently getting an 83.7% profit margin sounds like a good deal, but without knowing the costs of the other components (S3, EC2, data transfer) it’s difficult to conclude if this solution would remain profitable at a good margin. Anyway, an interesting aspect of this solution is that the costs of some major components of the platform (S3, DynamoDB) would scale lineary with the revenue.

Original title and link: A Cost Analysis of DynamoDB for Tarsnap (NoSQL database©myNoSQL)

via: http://www.daemonology.net/blog/2012-01-23-why-tarsnap-wont-use-dynamodb.html

A dynamo-as-a-service offered by Amazon on their ecosystem will appeal to some. For others, the benefits of a Dynamo-inspired product that can be deployed on other public clouds, behind-the-firewall, or not on the cloud at all, will be critical.

Objective. Clear. To the point.

Original title and link: Basho: Congratulations, Amazon! (NoSQL database©myNoSQL)

via: http://basho.com/blog/technical/2012/01/18/Congratulations-Amazon/

James Hamilton:

In a past blog entry, One Size Does Not Fit All, I offered a taxonomy of 4 different types of structured storage system, argued that Relational Database Management Systems are not sufficient, and walked through some of the reasons why NoSQL databases have emerged and continue to grow market share quickly. The four database categories I introduced were: 1) features-first, 2) scale-first, 3) simple structure storage, and 4) purpose-optimized stores. RDBMS own the first category.

DynamoDB targets workloads fitting into the Scale-First and Simple Structured storage categories where NoSQL database systems have been so popular over the last few years

A great post focusing on the challenges faced to implement the features that make DynamoDB, the Amazon cloud-based NoSQL database, unique.

Original title and link: Amazon DynamoDB: NoSQL in the Cloud (NoSQL database©myNoSQL)

via: http://perspectives.mvdirona.com/2012/01/18/AmazonDynamoDBNoSQLInTheCloud.aspx