Amazon Elastic MapReduce is a web service that enables businesses, researchers, data analysts, and developers to easily and cost-effectively process vast amounts of data. It utilizes a hosted Hadoop framework running on the web-scale infrastructure of Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3).

Using Amazon Elastic MapReduce, you can instantly provision as much or as little capacity as you like to perform data-intensive tasks for applications such as web indexing, data mining, log file analysis, machine learning, financial analysis, scientific simulation, and bioinformatics research. Amazon Elastic MapReduce lets you focus on crunching or analyzing your data without having to worry about time-consuming set-up, management or tuning of Hadoop clusters or the compute capacity upon which they sit.

Languages supported: Java, Ruby, Perl, Python, PHP, R, and C++.

Sorting on only one attribute is still quite limiting, though, and queries still only return object IDs, which forces many further queries to retrieve the full data-set.

Previously, disk storage on an EC2 was transient:- when the machine was shut down or crashed, it felt like a hard drive crash. (And you’d lose your IP address too, but Amazon added static IPs a little while ago too.) The path to reliability was to use S3, but that can’t be mounted as a native file system.

The persistent storage appears as a raw, mountable filesystem that needs to be formatted. You’ll be able to make a quick snapshot of the data, for backup. No word on pricing or its performance, but you’d expect it to be aligned with S3.

Google App Engine makes it easy to build an application that runs reliably, even under heavy load and with large amounts of data. The environment includes the following features:

• dynamic web serving, with full support for common web technologies
• persistent storage with queries, sorting and transactions
• automatic scaling and load balancing
• APIs for authenticating users and sending email using Google Accounts
• a fully featured local development environment that simulates Google App Engine on your compute

The main demo that Google have made for it, HuddleChat, is a direct, “feature for feature, layout for layout”, clone of 37signal’s Campfire, a great web chat application made by a company of 10. “We thought that would be beneath Google, but maybe its time to reevaluate what they stand for.”

Update: Google have taken down HuddleChat, citing widespread complaints.

Scalr is a fully redundant, self-curing and self-scaling hosting environment utilizing Amazon’s EC2.

It allows you to create server farms through a web-based interface using prebuilt AMI’s for load balancers (pound or nginx), app servers (apache, others), databases (mysql master-slave, others), and a generic AMI to build on top of.

The project is still very young, but we’re hoping that by open sourcing it the AWS development community can turn this into a robust hosting platform and give users an alternative to the current fee based services available.

This looks like it could be great when it develops. I kind of think that Amazon themselves should be providing this kind of executive service to auto-scale and -heal an application deployed in their grid (and wouldn’t be surprised if they add it as their service matures).

This makes EC2 much more viable for running public web sites, because now you can set up a load balancer on a static IP, and not have to worry about dynamic DNS, and clients that ignore TTLs.