Product: Amazon's SimpleDB

Update 35: How and Why Glue is Using Amazon SimpleDB instead of a Relational Database. Discusses a key design decision that required duplicating data in order to mimic RDBMS joins: Given the trade off between potential inconsistencies and scalability, social services have to choose the latter. Update 34: Apparently Amazon pulled this article. I'm not sure what that means. Maybe time went backwards or something? Amazon dramatically drops SimpleDB pricing to $0.25 per GB per month from $1.50 per GB. This puts SimpleDB on par with Google App Engine. They also announced a few new features: a SQL-like SELECT API as well as a Batch Put operation to streamline uploading of multiple items or attributes. One of the complaints against SimpleDB is that programmers end up writing too much code to do simple things. These features and a much cheaper price should help considerably. And you can store lots of data now. GAE is still capped. Update 33: Amazon announces Elastic Block Store (EBS), which provides lots of normal looking disk along with value added features like snapshots and snapshot copying. But database's may find EBS too slow. RightScale tells us Why Amazon’s Elastic Block Store Matters. Update 32: You can now get all attributes for a property when querying. Previously only the ID was returned and the attributes had to be returned in separate calls. This makes the programmer's job a lot simpler. Artificial levels of parallelization code can now be dumped. Update 31: Amazon fixes a major hole in SimpleDB by adding the ability to sort query results. Previously developers had to sort results by hand which was a non-starter for many. Now you can do basic top 10 type queries with ease. Update 30: Amazon SimpleDB - A distributed, highly-scalable, light-weight, query-able, attribute store by Sebastian Stadil. It introduces the CAP theorem and the basics of SimpleDB. Sebastian does a lot of great work in the AWS world and in what must be his limited free time, runs the AWS Meetup group. Update 29: A stroll down the history of a previous RDBMS killer, object databases. Lots of fond memories of the new kid on the block showing us how objects and code were one, the endless OO vs. relational wars, writing a OODBMS training course, dealing with object migration and querying etc, and the slow decline followed by groveling in front of the old master. It would be a terrible irony if a hash table succeeded where OODBMSs failed. Update 28: I didn't make the beta program :-( Update 27: IBM has hired CouchDB creator Damien Katz as their player in the game. Teams Microsoft, IBM, and Amazon have all entered the race. Amazon is 10 furlongs ahead, but watch for team Google, a fast finisher on the outside. Update 26: Red Monk says Microsoft's Astoria project is SDBish, but developers are afraid of lock-in. Update 25: Nati Shalom thinks SDB isn't even a database. Update 24: Igvita asks why do you need SDB when Thrudb is faster and cheaper? It provides a memcached layer in front of a database storing data in S3. And even better, all its service names start with "thru" instead of "S". Update 23: For all you Perl haters, the Perl interface to SDB is clean and beautiful. Update 22: On an Erlang email list Jim Larson says the proper model is to store bulk data in S3 and indexable metadata in SimpleDB. The cost of SimpleDB is 10x for storing data versus S3. We are supposed to build our own inverted index for text searching, which is one of those decisions that sounds good in the meeting room (yay, we don't have to do all that work), but is not a good decision in the real world. Update 21: Sensepost is already creating attack models to drain your bank account through repeated queries. Update 20: Grow some stones, smoothspan says Eventual Consistency Is Not That Scary. Update 19: Jacob Harris in A First Look at Amazon SimpleDB offers up some beta Ruby libraries for accessing SDB. Update 18: Erlang folks hope to get some run, but Erlang the language is too different to go mainstream, though Erlang's concurrency model rocks. A while back I talked about how The Solution to C++ Threading is Erlang and how Java's concurrency approach is fundamentally broken. Update 17: Subbu tirelessly provides a A RESTful version of Amazon's SimpleDB. Update 16: Snarfed sees it as a sort of tuplespace implementation. Compare it to Facebook's API. Ning also has a data API. Update 15: Uncom thinks Winer & Scoble Fail In Tandem. SDB's XML response has 1,755% transmission overhead, which is genius for a per byte pricing model. And I love this one: if you are starting a business whose success hinges on scalability of a data store, you had best figure out how to shard across N machines before you launch. Using a single instance of MySQL for the whole thing is a strong indicator that you have failed at life. Update 14: Styled Bits sees SDB as more of a way to add metadata to S3 objects. Update 13: Bex Huff makes the point you'll still need a caching layer in front of SDB. Update 12: Shahzad Bhatti has been coding for SimpleDB for a few months and gives us a cool Java and Erlang API for basic CRUD operations. Update 11: DBA4Life says Amazon has just flux capacited us back to 1980s style database management. Update 10: Bob Warfield of SmoothSpan explains Why the Amazon SimpleDB is a Huge Next Step. It helps achieve the necessary "16:1 operations cost advantages over conventional software." Update 9: SimpleDB is berkleyDB and 90% of all computing will live in cloud city. Will the Troglyte's revolt? Update 8: Dave Winer says Amazon removes the database scaling wall by adding a storage ramp that scales up when needed and scales down when unneeded. You no longer need to buy expensive VC funded database talent to take your product to the next level. Update 7: Kevin Burton in Google vs Amazon in Open Infrastructure has doubts about the entire hosted model. Bandwidth costs too much, it might hurt your acquisition chances, and you can't trust 'em. He just wants to lease managed raw machine power. Update 6: Amazon SimpleDB and CouchDB compared. Some key differences: SimpleDB is hosted. CouchDB is REST/JSON and SimpleDB is REST/SOAP/XML. In SimpleDB attribute updates are atomic in CouchDB record updates are atomic. CouchDB supports JSON data types and SimpleDB thinks everything is a string. CouchDB has much more flexible indexing and queries. Update 5: Sriram Krishnan gives a more technical overview of SimpleDB. He likes the big hash table approach and brings up how the query language allows for parallelization. Update 4: Mark from areyouwatchingthis.com makes a really insightful point: I run a startup that gets 75% of our traffic from our API. The ability to move that processing and storage into a cloud _might_ save me a lot on hosting. Update 3: Marcelo Calbucci thinks SimpleDB is more of a directory service than a database because records can contain different attributes (no schema) and attributes can have multiple values. Update 2: Smug Mugs' Don MacAskill likes the service, but is concerned that field sizes are limited to 1024 characters and latency from far away datacenters. He thinks most queries will be easy to convert as they are predominantly hash like lookups anyway. Update: Scoble asks if SimpleDB kills MySQL, Oracle, et al. The answer is no. Google has a similar service internally and they are still major users of and contributors to MySQL. Sometimes you just need structured data. So RDBMSs aren't dead. They just may not be the starting point as the barrier to entry for doing the simplest thing to start a website has plummeted. No more setup or admin. Just code and go. The cherry missing from Amazon's AWS hot fudge sundae was a database service. They had a CPU scoop with EC2, they had storage scoop with S3, they had a work distribution scoop with their queue, but the database cherry was missing. Now they've added it and it's dessert time. News of SimpleDB is everywhere. Apparently it's been in development for a while. You can read about it inside looking out, GIGAOM, Innowave, SimpleDB Developer's Guide, and the SimpleDB Home Page. It seems to be a simple properties like store implemented on Erlang (as is CouchDB). It has simple query capabilities on attributes. It's fast and scalable. And At $0.14 per hour it's quite competitive with other options. What it doesn't have is a text search or complex RDBMS style queries for structured data. It's not clear if the data are geographically distributed, in case you are interested in fast response times from different parts of the world. I would be very curious on the relationship between SimpleDB and Dynamo. Even with these limitations it's a disruptive service. Most high speed websites use a property store for unstructured data and that's been hard for smaller groups to implement at scale. But if you're losing your mind trying to figure out how to store your data at scale, maybe you can now turn your attention to more productive problems.

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Scalability Perspectives #5: Werner Vogels – The Amazon Technology Platform

Scalability Perspectives is a series of posts that highlights the ideas that will shape the next decade of IT architecture. Each post is dedicated to a thought leader of the information age and his vision of the future. Be warned though – the journey into the minds and perspectives of these people requires an open mind.

Werner Vogels

Dr. Werner Vogels is Vice President & Chief Technology Officer at Amazon.com where he is responsible for driving the company’s technology vision, which is to continuously enhance the innovation on behalf of Amazon’s customers at a global scale. Prior to joining Amazon, he worked as a researcher at Cornell University where he was a principal investigator in several research projects that target the scalability and robustness of mission-critical enterprise computing systems. He is regarded as one of the world's top experts on ultra-scalable systems and he uses his weblog to educate the community about issues such as eventual consistency. Information Week recently recognized Vogels for this educational and promotional role in Cloud Computing with the 2008 CIO/CTO of the Year award.

Service-Oriented Architecture, Utility Computing and Internet Level 3 Platform in practice

Amazon has built a loosely coupled service-oriented architecture on an inter-planetary scale. They are the pioneers of Utility Computing and Internet Platforms discussed earlier in Scalability Perspectives. Amazon's CTO, Werner Vogels is undoubtedly a thought leader for the coming age of cloud computing.

Cloud Computing CTO or Chief Cloud Officer?

Vogels' name and face are often associated with Amazon's cloud, but Amazon Web Services isn't a one-man show, it is Teamwork. Amazon's CTO has emerged as the right person at the right time and place to guide cloud computing - until now, an emerging technology for early adopters - into the mainstream. He not only understands how to architect a global computing cloud consisting of tens of thousands of servers, but also how to engage CTOs, CIOs, and other professionals at customer companies in a discussion of how that architecture could potentially change the way they approach IT. If all goes as planned, Amazon's cloud will serve as an extension of corporate data centers for new applications and overflow capacity, so-called cloud bursting. Over time, Amazon will then take on more and more of the IT workload from businesses that see value in the model. Customer-centric? What Amazon's doing goes beyond that. Amazon's cloud becomes their cloud; its CTO, their CTO. As an expert of distributed systems Vogels shares interesting insights on scalability related issues on his blog such as:

• A Word on Scalability
• Eventually Consistent
• Amazon's Dynamo

The Amazon Technology Platform

Werner Vogels explains how Amazon has become a platform provider, and how an increasing number of diverse businesses are built on the Amazon.com platform in this QCon presentation. The most important thing to understand is that Amazon is a Technology Platform with the emphasis on Technology. The scalable and reliable platform is the main enabler of Amazon's business model. Dr Werner describes Amazon’s platform business model and its ‘flywheel’ for growth on the latest episode of the Telco 2.0 ‘executive brainstorm’ series on Telecom TV. Amazon has many platforms that fuels growth such as:

• Amazon Merchants
• Amazon Associates
• Amazon E-Commerce Platform
• Web Scale Computing Platform
• Amazon Kindle
• Telecommunications platfrom using Amazon's platform?

Werner provides interesting insights about these platforms in his presentation. Check out his blog and other resources to learn more about his vision and Amazon's future.

Information Sources

• All Things Distributed - Werner Vogels' weblog on building scalable and robust distributed systems
• Werner Vogels on Wikipedia.org
• Information Week - Chief Of The Year: Amazon CTO Werner Vogels and related Q&A
• The Amazon.com Technology Platform: Building Blocks for Innovation
• Amazon's Platform Business Model
• Episode 40: Interview Werner Vogels
• ACM Queue - A conversation with Werner Vogels
• ITConversations: Supernova – Werner Vogels on Scalability
• Sell on Amazon: A Guide to Amazon's Marketplace, Seller Central, and Fulfillment by Amazon Programs
• Werner Vogels on Twitter

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100% on Amazon Web Services: Soocial.com - a lesson of porting your service to Amazon

Simone Brunozzi, technology evangelist for Amazon Web Services in Europe, describes how Soocial.com was fully ported to Amazon web services.

---------------- This period of the year I decided to dedicate some time to better understand how our customers use AWS, therefore I spent some online time with Stefan Fountain and the nice guys at Soocial.com, a "one address book solution to contact management", and I would like to share with you some details of their IT infrastructure, which now runs 100% on Amazon Web Services!

In the last few months, they've been working hard to cope with tens of thousands of users and to get ready to easily scale to millions. To make this possible, they decided to move ALL their architecture to Amazon Web Services. Despite the fact that they were quite happy with their previous hosting provider, Amazon proved to be the way to go. -----------------

Read the rest of the article here.

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Scalability Perspectives #1: Nicholas Carr – The Big Switch

Scalability Perspectives is a series of posts that highlights the ideas that will shape the next decade of IT architecture. Each post is dedicated to a thought leader of the information age and his vision of the future. Be warned though – the journey into the minds and perspectives of these people requires an open mind.

Nicholas Carr

A former executive editor of the Harvard Business Review, Nicholas Carr writes and speaks on technology, business, and culture. His provocative 2004 book Does IT Matter? set off a worldwide debate about the role of computers in business.

The Big Switch – Rewiring the World, From Edison to Google

Carr's core insight is that the development of the computer and the Internet remarkably parallels that of the last radically disruptive technology, electricity. He traces the rapid morphing of electrification from an in-house competitive advantage to a ubiquitous utility, and how the business advantage rapidly shifted from the innovators and early adopters to corporate titans who made their fortune from controlling a commodity essential to everyday life. He envisions similar future for the IT utility in his new book

• The Big Switch: Rewiring the World, from Edison to Google

... and likewise all parts of the system must be constructed with reference to all other parts, since, in one sense, all the parts form one machine. - Thomas Edison Carr's vision is that IT services delivered over the Internet are replacing traditional software applications from our hard drives. We rely on the new utility grid to connect with friends at social networks, track business opportunities, manage photo collections or stock portfolios, watch videos and write blogs or business documents online. All these services hint at the revolutionary potential of the new computing grid and the information utilities that run on it. In the years ahead, more and more of the information-processing tasks that we rely on, at home and at work, will be handled by big data centers located out on the Internet. The nature and economics of computing will change as dramatically as the nature and economics of mechanical power changed with the rise of electric utilities in the early years of the last century. The consequences for society - for the way we live, work, learn, communicate, entertain ourselves, and even think - promise to be equally profound. If the electric dynamo was the machine that fashioned twentieth century society - that made us who we are - the information dynamo is the machine that will fashion the new society of the twenty-first century. The utilitarians as Carr calls them can deliver breakthrough IT economics through the use of highly efficient data centers and scalable, distributed computing, networking and storage architecture. There's a new breed of Internet company on the loose. They grow like weeds, serve millions of customers a day and operate globally. And they have very, very few employees. Look at YouTube, the video network. When it was bought by Google in 2006, for more than $1 billion, it was one of the most popular and fastest growing sites on the Net, broadcasting more than 100 million clips a day. Yet it employed a grand total of 60 people. Compare that to a traditional TV network like CBS, which has more than 23,000 employees.

Goodbye, Mr. Gates

So is the title for Chapter 4 of the book. “The Next Sea change is upon us.” Those words appeared in an extraordinary memorandum that Bill Gates sent to Microsoft's top managers and engineers on October 30, 2005. “Services designed to scale to tens or hundreds of millions [of users] will dramatically change the nature and cost of solutions deliverable to enterprise or small businesses.” This new wave, he concluded, “will be very disruptive.”

IT in 2018: From Turing’s Machine to the Computing Cloud

Carr's new internet.com eBook concludes that thanks to the theory of Alan Turing's Universal Computing Machine and the rise of modern virtualization technologies:

• With enough memory and enough speed, Turing’s work implies, a single computer could be programmed, with software code, to do all the work that is today done by all the other physical computers in the world.
• Once you virtualize the computing infrastructure, you can run any application, including a custom-coded one, on an external computing grid.
• In other words: Software (coding) can always be substituted for hardware (switching).

Into the Cloud

Carr demonstrates the power of the cloud through the example of the answering machine which have been vaporized into the cloud. This is happening to our e-mails, documents, photo albums, movies, friends and world (google earth?), too. If you’re of a certain age, you’ll probably remember that the first telephone answering machine you used was a bulky, cumbersome device. It recorded voices as analog signals on spools of tape that required frequent rewinding and replacing. But it wasn’t long before you replaced that machine with a streamlined digital answering machine that recorded messages as strings of binary code, allowing all sorts of new features to be incorporated into the device through software programming. But the virtualization of telephone messaging didn’t end there. Once the device became digital, it didn’t have to be a device anymore – it could turn into a service running purely as code out in the telephone company’s network. And so you threw out your answering machine and subscribed to a service. The physical device vaporized into the “cloud” of the network.

The Great Enterprise of the 21st Century

Carr considers building scalable web sites and services a great opportunity for this century. Good news for highscalability.com :-) Just as the last century’s electric utilities spurred the development of thousands of new consumer appliances and services, so the new computing utilities will shake up many markets and open myriad opportunities for innovation. Harnessing the power of the computing grid may be the great enterprise of the twenty-first century.

Information Sources

• The Big Switch: Rewiring the World, from Edison to Google
• Does IT Matter? Information Technology and the Corrosion of Competitive Advantage
• IT in 2018: From Turing’s Machine to the Computing Cloud
• Rough Type: Nicholas Carr's Blog

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Scalr - Open Source Auto-scaling Hosting on Amazon EC2

Scalr is a fully redundant, self-curing and self-scaling hosting environment utilizing Amazon's EC2. It has been recently open sourced on Google Code. Scalr 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. Scalr promises automatic high-availability and scaling for developers by health and load monitoring. The health of the farm is continuously monitored and maintained. When the Load Average on a type of node goes above a configurable threshold a new node is inserted into the farm to spread the load and the cluster is reconfigured. When a node crashes a new machine of that type is inserted into the farm to replace it. 4 AMI's are provided for load balancers, mysql databases, application servers, and a generic base image to customize. Scalr allows you to further customize each image, bundle the image and use that for future nodes that are inserted into the farm. You can make changes to one machine and use that for a specific type of node. New machines of this type will be brought online to meet current levels and the old machines are terminated one by one. The open source scalr platform with the combination of the static EC2 IP addresses makes elastic computing easier to implement. Check out the blog announcement by Intridea for more info. As AWS conquers the scalable web application hosting space it is time to check out the new Programming Amazon Web Services: S3, EC2, SQS, FPS, and SimpleDB (Programming) book on amazon.com. What do you think of the opportunities of using scalr for automatic scalability?

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Amazon Announces Static IP Addresses and Multiple Datacenter Operation

Amazon is fixing two of their major problems: no static IP addresses and single datacenter operation. By adding these two new features developers can finally build a no apology system on Amazon. Before you always had to throw in an apology or two. No, we don't have low failover times because of the silly DNS games and unexceptionable DNS update and propagation times and no, we don't operate in more than one datacenter. No more. Now Amazon is adding Elastic IP Addresses and Availability Zones. Elastic IP addresses are far better than normal IP addresses because they are both in tight with Jessica Alba and they are: Static IP addresses designed for dynamic cloud computing. An Elastic IP address is associated with your account, not a particular instance, and you control that address until you choose to explicitly release it. Unlike traditional static IP addresses, however, Elastic IP addresses allow you to mask instance or availability zone failures by programmatically remapping your public IP addresses to any instance associated with your account. Rather than waiting on a data technician to reconfigure or replace your host, or waiting for DNS to propagate to all of your customers, Amazon EC2 enables you to engineer around problems with your instance or software by programmatically remapping your Elastic IP address to a replacement instance. About the new feature RightScale says: Amazon did a very nice job in creating something much more powerful than simply adding “static IPs” to their offering. They are giving us dynamically remappable IP addresses that fit well into the overall cloud computing paradigm that we can use to manage servers better than with traditional hosting solutions. Mostly good news. It's not great news because RightScale also says "Assigning or reassigning an IP to an instance takes a couple of minutes..." So it's not as speedy as one would hope, but at least you don't have to wait for TTL to kick in and everyone up and down the stack to get new IP addresses. Cached static IP addresses will always be valid, which simplifies and speeds things up considerably, especially when using redundant load balancers as the entry point into your system. The other power feature added was the ability to specify which datacenter your instances run in. Amazon calls this feature Availability Zones: Availability Zones provide the ability to place instances in multiple locations. Amazon EC2 locations are composed of regions and availability zones. Regions are geographically dispersed and will be in separate geographic areas or countries. Currently, Amazon EC2 exposes only a single region. Availability zones are distinct locations that are engineered to be insulated from failures in other availability zones and provide inexpensive, low latency network connectivity to other availability zones in the same region. Regions consist of one or more availability zones. By launching instances in separate availability zones, you can protect your applications from failure of a single location. You might also be wondering how fast connections are between datacenters. They are said to be: "inexpensive, low latency network connectivity to other availability zones in the same region." I tend to believe this. I've been surprised before how fast datacenter links can be in that you didn't have code specially for these configurations. How this will impact S3 and SimpleDB latencies is an interesting question. And how system design will need to change once datacenters are in different regions of the world is another interesting question. Other services still have more datacenters, more geographically dispersed datacenters than Amazon, and better content migration capabilities, but this is a great first step that allows developers to add another layer of reliability to their systems. Update: I thought this was a good explanation of using static IPs in Some more about EC2: Slashdot hasn't run many stories on EC2 (none that I know of) because until now it's been a niche service. Without a way to guarantee that you can have a static IP, there had been a single point of failure: if your outward-facing VMs all went down, your only recourse was to start up more VMs on new, dynamically-assigned IPs, point your DNS to them, and wait hours for your users' DNS caches to expire. That meant that while it may have been a good service for sites that needed to do massive private computation, it was an unacceptable hosting service. Now with static IPs, you basically set up your service to have several VMs which provide the outward-facing service (maybe running a webserver, or a reverse proxy for your internal webservers), and you point your public, static IPs at those. If one or more of them goes down, you start up new copies of those VMs and repoint the IPs to them. No DNS changes required.

Related Articles

Jesse Robbins links to a good explanation by RightScale of Availability Zones: Setting up a fault-tolerant site using Amazon’s Availability Zones.

RightScale also writes DNS, Elastic IPs (EIP) and how things fit together when upgrading a server

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Streaming Video on Amazon EC2?

An Amazon EC2 Flash Video Streaming solution has been announced by Wowza Media. What do you think about the future of similar solutions? Is Amazon EC2 and S3 ready for video streaming? I have found threads on their forums related to the performance, scalability and high availability of the hosted streaming solution. How would you make it scalable? Is it really cheaper than traditional hosting? Looking forward to your thoughts!

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The Current Pros and Cons List for SimpleDB

Not surprisingly opinions on SimpleDB vary from it sucks, don't take my database, to it will change the world, who needs a database anyway? From a quick survey of the blogosphere, here's where SimpleDB stands at the moment:

SimpleDB Cons

No SLA. We don't know how reliable it will be, how fast it will be, or how consistent the performance will be.

Consistency constraints are relaxed. Reading data immediately after a write may not reflect the latest updates. To programmers used to transactions, this may be surprising, but many people think this is one of the tradeoffs that needs to be made to scale.

Database is a core competency. If you don't control your database you can't out compete your competition.

When your database is out of your control you can't guarantee it will work properly. You can't create the proper indexes and other optimizations.

No join or IN operator. You'll need to do multiple client side calls to simulate joins, which will be slow.

No stored procedures, referential integrity, and other relational goodies. This is not a professional product.

Attribute size limited to 1024 bytes. It's not designed for content serving.

Latency from outside Amazon will be high.

Setting up and maintaining a database is cheap and easy these days, so why bother? It costs too much compared when compared to running your own servers.

What happens when you need to super scale to very large datasets?

No API support from common languages like PHP, Ruby, etc.

All your existing code and infrastructure needs to be rewritten.

Not geographically distributed with nearest datacenter routing.

Queries are lexigraphical. So you’ll need to store data in lexicographical order. This means says inside looking out: zero-padding your integers, adding positive offsets to negative integer sets, and converting dates into something like ISO 8601.

Attribute values are typeless which could lead to a lot of typing related errors and inefficient queries.

The 10 GB maximum per domain is too limiting.

It's not Dynamo. Amazon is keeping the really good stuff to themselves.

Text searching is not supported. You'll need to construct your own fast search indexes.

Queries are limited to 5 seconds running time. It's only for getting and setting, nothing more SQLish.

No cloned APIs for unit testing. Need to be able to develop locally against other data stores.

Your data is under Amazon's control, so there could be security and privacy problems.

The XML based protocol unnecessarily increases overhead, latency, and cost.

Lockin. If you decide to leave Amazon’s cloud how do you move all your data and get a similar system up and working outside the cloud?

Open cash register. Since SDB is charge on use, a malicious user can simply setup a loop to query your site, which costs you an unbounded amount of money.

SimpleDB Pros

SimpleDB is not a relational database. Relational databases are too complex and don't scale well. Keeping data access simple is a selling point, not a weakness.

Low setup costs and pay-as-you-go expansion make it perfect for startups. The price is reasonable given the functionality and the hands off admin.

Setting up and maintaining a highly available clustered database that is constantly growing is extremely difficult. Building your application on a building block that does all this for you adds a lot of value.

Setting up a database inside EC2 is a pain. The makes getting basic database functionality trivial. No need to worry about scaling, capacity planning, or partitioning.

It has a decent query language, which is unusual for this type of data store.

Data are stored across multiple nodes which supports parallel query execution.

It's built on Erlang and that's cool.

You don't need to seek funding to hire a database team and buy hardware. Depending on how you weight each factor, SimpleDB could be way behind or way ahead of other options. What's interesting is to see what people think is important. For many people the only real database is relational and if it doesn't have transactions, joins, etc it's not real. Databases like beauty seem to be in the eye of the beholder.

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Amazon SimpleDB - Scalable Cloud Database

Amazon has announced the limited beta of Amazon SimpleDB - a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Together with the Simple Storage Service (S3), Elastic Compute Cloud (EC2) and other web services Amazon offers a complete utility computing platform. SimpleDB was the missing piece of AWS - the scalable structured database. Check out my blog entry: http://innowave.blogspot.com/2007/12/amazon-simpledb-scalable-cloud-database.html I was waiting for this one :-) Geekr

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