The Complete Guide to Building Cloud Computing Solutions with Amazon SimpleDB. 'Introducing Amazon SimpleDB' is extracted from 'A Developer's Guide to Amazon SimpleDB', published by Addison-Wesley Professional.
The Complete Guide to Building Cloud Computing Solutions with Amazon SimpleDB. 'Introducing Amazon SimpleDB' is extracted from 'A Developer's Guide to Amazon SimpleDB', published by Addison-Wesley Professional.
has been offering its customers computing infrastructure via Amazon Web
Services (AWS) since 2006. AWS aims to use its own infrastructure to provide
the building blocks for other organizations to use. The Elastic Compute Cloud
(EC2) is an AWS offering that enables you to spin up virtual servers as you
need the computing power and shut them off when you are done. Amazon Simple
Storage Service (S3) provides fast and unlimited file storage for the web.
Amazon SimpleDB is a service designed to complement EC2 and S3, but the concept
is not as easy to grasp as extra servers and extra storage. This chapter
will cover the concepts behind SimpleDB and discuss how it compares to other
What Is SimpleDB?
SimpleDB is a web service providing structured data storage
in the cloud and backed by clusters of Amazon-managed database servers. The
data requires no schema and is stored securely in the cloud. There is a query
function, and all the data values you store are fully indexed. In keeping with
Amazons other web services, there is no minimum charge, and you are only
billed for your actual usage.
What SimpleDB Is Not
The name SimpleDB might lead you to believe that it is just
like relational database management systems (RDBMS), only simpler to use. In some
respects, this is true, but it is not just about making simplistic database usage
simpler. SimpleDB aims to simplify the much harder task of creating and managing
a database cluster that is fault-tolerant in the face of multiple failures, replicated
across data centers, and delivers high levels of availability.
One misconception that seems to be very common among people
just learning about SimpleDB is the idea that migrating from an RDBMS to
SimpleDB will automatically solve your database performance problems.
Performance certainly is an important part of the equation when you seek to
evaluate databases. Unfortunately, for some people, speed is the beginning and
the end of the thought process. It can be tempting to view any of the new
hosted database services as a silver bullet when offered by a mega-company like
Microsoft, Amazon, or Google. But the fact is that SimpleDB is not going to
solve your existing speed issues. The service exists to solve an entirely
different set of problems. Reads and writes are not blazingly fast. They are
meant to be fast enough. It is entirely possible that AWS may increase
performance of the service over time, based on user feedback. But SimpleDB is
never going to be as speedy as a standalone database running on fast hardware.
SimpleDB has a different purpose.
Robust database clusters replicating data across multiple data
centers is not a data storage solution that is typically easy to throw
together. It is a time consuming and costly undertaking. Even in organizations
that have the database administrator (DBA) expertise and are using multiple
data centers, it is still time consuming. It is costly enough that you would
not do it unless there was a quantifiable business need for it. SimpleDB offers
data storage with these features on a pay-as-you-go basis.
Of course, taking advantage of these features is not without a
downside. SimpleDB is a moderately restrictive environment, and it is not
suitable for many types of applications. There are various restrictions and
limitations on how much data can be stored and transferred and how much network
bandwidth you can consume.
SimpleDB differs from relational databases where you must
define a schema for each database table before you can use it and where you
must explicitly change that schema before you can store your data differently.
In SimpleDB, there is no schema requirement. Although you still have to consider
the format of your data, this approach has the benefit of freeing you from the
time it takes to manage schema modifications.
The lack of schema means that there are no data types; all data
values are treated as variable length character data. As a result, there is
literally nothing extra to do if you want to add a new field to an existing
database. You just add the new field to whichever data items require it. There
is no rule that forces every data item to have the same fields.
The drawbacks of a schema-less database include the lack of automatic
integrity checking in the database and an increased burden on the application to
handle formatting and type conversions. Detailed coverage of the impact of schema-less
data on queries appears in Chapter 4, A Closer Look at Select, along with a discussion
of the formatting issues.
Stored Securely in the Cloud
The data that you store in SimpleDB is available both from the
Internet and (with less latency) from EC2. The security of that data is of great
importance for many applications, while the security of the underlying web services
account should be important to all users.
To protect that data, all access to SimpleDB, whether read or
write, is protected by your account credentials. Every request must bear the
correct and authorized digital signature or else it is rejected with an error
code. Security of the account, data transmission, and data storage is the
subject of Chapter 8, Security in SimpleDB-Based Applications.
Billed Only for Actual Usage
In keeping with the AWS philosophy of pay-as-you-go,
SimpleDB has a pricing structure that includes charges for data storage, data
transfer, and processor usage. There are no base fees and there are no
minimums. At the time of this writing, Amazons monthly billing for SimpleDB
has a free usage tier that covers the first gigabyte (GB) of data storage, the
first GB of data transfer, and the first 25 hours of processor usage each
month. Data transfer costs beyond the free tier have historically been on par with
S3 pricing, whereas storage costs have always been somewhat higher. Consult the
AWS website at https://aws.
amazon.com/simpledb/ for current pricing information.
Domains, Items, and Attribute Pairs
The top level of data storage in SimpleDB is the domain. A domain
is roughly analogous to a database table. You can create and delete domains as needed.
There are no configuration options to set on a domain; the only parameter you can
set is the name of the domain.
All the data stored in a SimpleDB domain takes the form of
name-value attribute pairs. Each attribute pair is associated with an item,
which plays the role of a table row. The attribute name is similar to a
database column name but unlike database rows that must all have identical
columns, SimpleDB items can each contain different attribute names. This gives
you the freedom to store different data in some items without changing the
layout of other items that do not have that data. It also allows the painless
addition of new data fields in the future.
It is possible for each attribute to have not just one
value, but an array of values. For example, an application that allows user
tagging can use a single attribute named tags to hold as many or as few tags
as needed for each item. You do not need to change a schema definition to
enable multi-valued attributes. All you need to do is add another attribute to
an item and use the same attribute name with a different value. This provides
you with flexibility in how you store your data.
SimpleDB is primarily a key-value
store, but it also has useful query functionality. A SQL-style query language is
used to issue queries over the scope of a single domain. A subset of the SQL select
syntax is recognized. The following is an example SimpleDB select statement:
SELECT * FROM products WHERE rating > '03' ORDER BY rating LIMIT 10
You put a domain namein this
case, productsin the FROM clause where a table name would normally be. The WHERE
clause recognizes a dozen or so comparison operators, but an attribute name
must always be on the left side of the operator and a literal value must always
be on the right. There is no relational comparison between attributes allowed
here. So, the following is not valid:
SELECT * FROM users WHERE creation-date = last-activity-date
All the data stored in SimpleDB is treated as plain string
data. There are no explicit indexes to maintain; each value is automatically
indexed as you add it.
High availability is an important benefit of using SimpleDB.
There are many types of failures that can occur with a database solution that
will affect the availability of your application. When you run your own
database servers, there is a spectrum of different configurations you can
To help quantify the availability benefits that you get
automatically with SimpleDB, lets consider how you might achieve the same
results using replication for your own database servers. At the easier end of
the spectrum is a master-slave database replication scheme, where the master
database accepts client updates and a second database acts as a slave and pulls
all the updates from the master. This eliminates the single point of failure.
If the master goes down, the slave can take over. Managing these failures (when
not using SimpleDB) requires some additional work for swapping IP addresses or
domain name entries, but it is not very difficult.
Moving toward the more difficult end of the self-managed replication
spectrum allows you to maintain availability during failure that involves more than
a single server. There is more work to be done if you are going to handle two servers
going down in a short period, or a server problem and a network outage, or a problem
that affects the whole data center.
Creating a database solution that maintains uptime during these
more severe failures requires a certain level of expertise. It can be
simplified with cloud computing services like EC2 that make it easy to start
and manage servers in different geographical locations. However, when there are
many moving parts, the task remains time consuming. It can also be expensive.
When you use SimpleDB, you get high availability with your data
replicated to different geographic locations automatically. You do not need to
do any extra work or become an expert on high availability or the specifics of
replication techniques for one vendors database product. This is a huge
benefit not because that level of expertise is not worth attaining, but because
there is a whole class of applications that previously could not justify that
One of the consequences of replicating database updates
across multiple servers and data centers is the need to decide what kind of
consistency guarantees will be maintained. A database running on a single
server can easily maintain strong consistency. With strong consistency, after
an update occurs, every subsequent database access by every client reflects the
change and the previous state of the database is never seen.
This can be a problem for a database cluster if the purpose of
the cluster is to improve availability. If there is a master database
replicating updates to slave databases, strong consistency requires the slaves
to accept the update at the same time as the master. All access to the database
would then be strongly consistent. However, in the case of a problem preventing
communication between the master and a slave, the master would be unable to
accept updates because doing so out of sync with a slave would break the
consistency guarantee. If the database rejects updates during even simple
problem scenarios, it defeats the availability. In practice, replication is
often not done this way. A common solution to this problem is to allow only the
master database to accept updates and do so without direct contact with any
slave databases. After the master commits each transaction, slaves are sent the
update in near real-time. This amounts to a relaxing of the consistency
guarantee. If clients only connect to the
slave when the master goes down, then the weakened consistency only applies to
SimpleDB sports the option of either eventual consistency or
strong consistency for each read request. With eventual consistency, when you
submit an update to SimpleDB, the database server handling your request will
forward the update to the other database servers where that domain is
replicated. The full update of all replicas does not happen before your update
request returns. The replication continues in the background while other
requests are handled. The period of time it takes for all replicas to be
updated is called the eventual consistency window. The eventual consistency
window is usually small. AWS does not offer any guarantees about this window,
but it is frequently less than one second.
A couple things can make the consistency window larger. One is
a high request load. If the servers hosting a given SimpleDB domain are under
heavy load, the time it takes for full replication is increased. Additionally a
network or server failure can block replication until it is resolved. Consider
a network outage between data centers hosting your data. If the SimpleDB
load-balancer is able to successfully route your requests to both data centers,
your updates will be accepted at both locations. However, replication will fail
between the two locations. The data you fetch from one will not be consistent
with updates you have applied to the other. Once the problem is fixed, SimpleDB
will complete the replication automatically.
Using a consistent read eliminates the consistency window for that
request. The results of a consistent read will reflect all previous writes. In
the normal case, a consistent read is no slower than an eventually consistent
read. However, it is possible for consistent read requests to display higher
latency and lower bandwidth on occasion.
Sizing Up the SimpleDB Feature Set
The SimpleDB API exposes a
limited set of features. Here is a list of what you get:
can create named domains within your account. At the time of this writing, the
initial allocation allows you to create up to 100 domains. You can request a
larger allocation on the AWS website.
- You can delete an
existing domain at any time without first deleting the data stored in it.
- You can store a
data item for the first time or for subsequent updates using a call to PutAttributes. When you
issue an update, you do not need to pass the full item; you can pass just the
attributes that have changed.
- There is a batch
call that allows you to put up to 25 items at once.
- You can retrieve
the data with a call to GetAttributes.
- You can query
for items based on criteria on multiple attributes of an item.
- You can store
any type of data. SimpleDB treats it all as string data, and you are free to
format it as you choose.
can store different types of items in the same domain, and items of the same
type can vary in which attributes have values.
Benefits of Using SimpleDB
When you use SimpleDB, you
give up some features you might otherwise have, but as a trade-off, you gain
some important benefits, as follows:
- AvailabilityWhen you store your data in SimpleDB, it
is automatically replicated across multiple storage nodes and across multiple data
centers in the same region.
- SimplicityThere are not a lot of knobs or dials,
and there are not any configuration parameters. This makes it a lot harder to
shoot yourself in the foot.
- ScalabilityThe service is designed for scalability
and concurrent access.
- FlexibilityStore the data you need to store now,
and if the requirements change, store it differently without changing the
- Low latency within the same regionAccess to
SimpleDB from an EC2 instance in the same region has the latency of a typical
- Low maintenanceMost of the administrative burden
is transferred to Amazon. They maintain the hardware and the database software.
Database Features SimpleDB Doesnt Have
There are a number of common
database features noticeably absent from Amazon SimpleDB. Programs based on
relational database products typically rely on these features. You should be
aware of what you will not find in SimpleDB, as follows:
- Full SQL supportA query language similar to SQL is
supported for queries only. However, it only applies to select statements,
and there are some syntax differences and other limitations.
- JoinsYou can issue queries, but there are no
foreign keys and no joins.
- Auto-incrementing primary keysYou have to create
your own primary keys in the form of an item name.
- TransactionsThere are no explicit transaction
boundaries that you can mark or isolation levels that you can define. There is
no notion of a commit or a rollback. There is some implicit support for atomic
writes, but it only applies within the scope of each individual item being
Higher-Level Framework Functionality
This simplicity of what SimpleDB offers on the server side is
matched by the simplicity of what AWS provides in officially supported SimpleDB
clients. There is a one-to-one mapping of service features to client calls. There
is a lot of functionality that can be built atop the basic SimpleDB primitives.
In addition, the inclusion of these advance features has already begun with a number
of third-party SimpleDB clients. Popular persistence frameworks used as an abstraction
layer above relational databases are prime candidates for this.
Some features normally included
within the database server can be written into SimpleDB clients for automatic
handling. Third-party client software is constantly improving, and some of the
following features may be present already or you may have to write it for
- Data formattingIntegers, floats, and dates require
special formatting in some cases.
- Object mappingIt can be convenient to map
programming language objects to SimpleDB attributes.
- ShardingThe domain is the basic unit of horizontal
scalability in SimpleDB. However, there is no explicit support for automatically
distributing data across domains.
- Cache integrationCaching is an important aspect of
many applications, and caching popular data objects is a well-understood
optimization. Configurable caching that is well integrated with a SimpleDB
client is an important feature.
There are quite a few limitations
on what you are allowed to do with SimpleDB. Most of these are size and
quantity restrictions. There is an underlying philosophy that small and quickly
serviced units of work provide the greatest opportunity for load balancing and
maintaining uniform service levels. AWS maintains a current listing of the
service limitations within the latest online SimpleDB Developer Guide at the
AWS website. At the time of this writing, the limits are as follows:
storage per domain: 10GB
- Max attribute values
per domain: 1 billion
- Initial max
domains per account: 100
- Max attribute
values per item: 256
- Max length of
item name, attribute name, or value: 1024 bytes
- Max query
execution time: 5 seconds
- Max query
- Max query response
comparisons per query: 20
These limits may seem restrictive when compared to the
unlimited nature of data sizes you can store in other database offerings.
However, there are two things to keep in mind about these limits. First, SimpleDB
is not a general-purpose data store suitable for everything. It is specifically
designed for storing small chunks of data. For larger data objects that you
want to store in the cloud, you are advised to use Amazon S3. Secondly,
consider the steps that need to be taken with a relational database at higher
loads when performance begins to degrade. Typical recommendations often include
offloading processing from the database, reducing long-running queries, and
applying selective de-normalization of the data. These limits are what help
enable efficient and automatic background replication and high concurrency and
availability. Some of these limits can be worked around to a degree, but no
workarounds exist for you to make SimpleDB universally appropriate for all data
Abandoning the Relational Model?
There have been many recent products and services offering
data storage but rejecting the relational model. This trend has been dubbed by
some as the NoSQL movement. There is a fair amount of enthusiasm both for and
against this trend. A few of those in the against column argue that databases
without schemas, type checking, normalization, and so on are throwing away 40
years of database progress. Likewise, some proponents are quick to dispense the
hype about how a given NoSQL solution will solve your problems. The aim of this
section is to present a case for the value of a service like SimpleDB that
addresses legitimate criticism and avoids hype and exaggeration.
A Database Without a Schema
One of the primary areas of contention around SimpleDB and
other NoSQL solutions centers on the lack of a database schema. Database
schemas turn out to be very important in the relational model. The formalism of
predefining your data model into a schema provides a number of specific
benefits, but it also imposes restrictions.
SimpleDB has no notion of a schema at all. Many of the
structures defined in a typical database schema do not even exist in SimpleDB.
This includes things such as stored procedures, triggers, relationships, and
views. Other elements of a database schema like fields and types do exist in
SimpleDB but are flexible and are not enforced on the server. Still other
features, like indexes, require no formal definition because the SimpleDB
service creates and manages them behind the scenes.
However, the lack of a schema requirement in SimpleDB does not
prevent you from gaining the benefits of a schema. You can create your own
schema for whatever portion of your data model that is appropriate. This allows
you to cherry-pick the benefits that are helpful to your application without
the unneeded restrictions.
One of the most important things you gain from codifying your
data layout is a separation between it and the application. This is an enabling
feature for tools and application plug-ins. Third-party tools can query your
data, convert your data from one format to another, and analyze and report on
your data based solely on the schema definition. The alternative is less
attractive. Tools and extensions are more limited in what they can do without
knowledge of the formats. For example, you cannot compute the sum of values in
a numeric column if you do not know the format of that column. In the
degenerate case, developers must search through your source code to infer data
In SimpleDB, many of the most common database features are not
available. Query, however, is one important feature that is present and has
some bearing on your data formatting. Because all the data you store in
SimpleDB is variable length character data, you must apply padding to numeric
data in order for queries to work properly. For example, if you want to store
an attribute named price with a value of 269.94, you must first add leading
zeros to make it 00000269.94. This is required because greater-than and
less-than comparisons within SimpleDB compare each character from left to
right. Padding with zeros allows you to line up the decimal point so the
comparisons will be correct for all possible values of that attribute.
Relational database products handle this for you behind the scenes when you
declare a column type is a numeric type like int.
This is a case in SimpleDB where a schema is beneficial. The
code that initially imports records into SimpleDB, the code that writes records
as your app runs, and any code that uses a numeric attribute in a query all
need to use the exact same format. Explicitly storing the schema externally is
a much less error-prone approach than implicitly defining the format in
duplicated code across various modules.
Another benefit of the predefined schema in the relational
model is that it forces you to think through the data relationships and make
unambiguous decisions about your data layout. Sometimes, however, the data is
simple, there are no relationships, and creating a data model is overkill.
Sometimes you may still be in the process of defining the data model. SimpleDB
can be used as part of the prototyping process, enabling you to evolve your
schema dynamically as issues surface that may not otherwise have become known
so quickly. You may be migrating from a different database with an existing
data model. The important thing to remember is that SimpleDB is simple by
design. It can be useful in a variety of situations and does not prevent you
from creating your own schema external to SimpleDB.
Areas Where Relational Databases Struggle
Relational databases have been around for some time. There
are many robust and mature products available. Modern database products offer a
multitude of features and a host of configuration options.
One area where difficulty arises is with database features that
you do not need or that you should not use for a particular application. Applications
that have simple data storage requirements do not benefit from the myriad of available
options. In fact, it can be detrimental in a couple different ways. If you need
to learn the intricacies of a particular database product before you can make good
use of it, the time spent learning takes away from time you could have spent on
your application. Knowledge of how database products work is good to have. It would
be hard to argue that you wasted your time by learning it because that information
could serve you well far into the future. Similarly, if there is a much simpler
solution that meets your needs, you could choose that instead. If you had no immediate
requirement to gain product specific database expertise, it would be hard to insist
that you made the wrong choice. It is a tough sell to argue that the more time-consuming,
yet educational, route is always better than the simple and direct route. This is
a challenge faced by databases today, when the simple problems are not met with
Another pain point with relational databases is horizontal
scaling. It is easy to scale a database vertically by beefing up your server
because memory and disk drives are inexpensive. However, scaling a database
across multiple servers can be extremely difficult. There is a whole spectrum
of options available for horizontal scaling that includes basic master-slave
replication as well as complicated sharding strategies. These solutions each
require a different, and sometimes considerable, amount of expertise.
Nevertheless, they all have one thing in common when compared to vertical
scaling solutions. On top of the implementation difficulty, each additional
server results in an additional increase in ongoing maintenance responsibility.
Moreover, it is not merely the additional server maintenance of having more
servers. I am referring to the actual database administration tasks of managing
additional replicas, backups, and log shipping. It also includes the tasks of
rolling out schema changes and new indexes to all servers in the cluster.
If you are in a situation where you want a simple database
solution or you want horizontal scaling, SimpleDB is definitely a service to
consider. However, you may need to be prepared to defend your decision.
Scalability Isnt Your Problem
Around every corner, you can find people who will challenge
your efforts to scale horizontally. Beyond the cost and difficulty, there is a
degree of resistance to products and services that seek to solve these
The typical, and now clichéd, advice tends to be that
scalability is not your problem, and trying to solve scalability at the outset
is a case of premature optimization. This is followed by a discussion of how
many daily page views a single high-performance database server can support. Finally,
it ends by noting that it is really just a problem for when you reach the scale
of Google or Amazon.
The premise of the argument is actually solid, although not
applicable to all situations. The premise is that when you are building a site
or service that nobody has heard of yet, you are more concerned about handling
loads of people than about making the site remarkable. It is good advice for
these situations. Moreover, it is especially timely considering that there is a
small but religious segment of Internet commentators who eagerly chime, X
doesnt scale, where X is any alternative to the solution the commenter uses.
Among programmers, there is a general preoccupation with performance
optimization that seems somewhat out of balance.
The fact is that for many projects, scalability really is not your
problem, but availability can be. Distributing your data store across servers from
the outset is not a premature optimization when you can quantify the cost of down
time. If a couple hours of downtime will have an impact on your business, then availability
is something worth thinking about. For the IT department delivering a mission-critical
application, availability is important. Even if only 20 users will use it during
normal business hours, when it provides a competitive advantage, it is important
to maintain availability through expected outages. When you have a product launch,
and your credibility is at stake as much as your revenue, you are not putting the
cart before the horse when you protect yourself against hardware failures.
There are many situations where availability is an important
system quality. Look at how common it is for a multi-server web cluster to host
one website. Before you can add a second web server, you must first solve a
small set of known problems. User sessions have to be managed properly; load
balancing has to be in place and routing around unresponsive servers. However,
web server clusters are useful for more than high-traffic load handling. They
are also beneficial because we know that hardware will fail, and we want to
maintain service during the failure. We can add another web server because it
is neither costly nor difficult, and it improves the availability. With the
advent of systems designed to provide higher database availability that are not
costly nor hard, availability becomes worth pursuing for less-critical projects.
Avoiding the SimpleDB Hype
There are many different application scenarios where
SimpleDB is an interesting option. That said, some people have overstated the
benefits of using SimpleDB specifically and hosted NoSQL databases in general.
The reasoning seems to be that services running on the infrastructure of
companies like Amazon, Google, or Microsoft will undoubtedly have nearly
unlimited automatic scalability. Although there is nothing wrong with
enthusiasm for products and services that you like, it is good to base that
enthusiasm on reality.
Do not be fooled into thinking that any of these new databases
is going to be a panacea. Make sure you educate yourself about the pros and
cons of each solution as you evaluate it. The majority of services in this space
have a free usage tier, and all the open-source alternatives are completely
free to use. Take advantage of it, and try them out for yourself. We live in an
amazing time in history where the quantity of information available at our
fingertips is unprecedented. Access to web-based services and open-source
projects is a huge opportunity. The tragedy is that in a time when it has never
been easier to gain personal experience with new technology, all too often we
are tempted to adopt the opinions of others instead of taking the time to form
our own opinions. Do not believe the hypefind out for yourself.
Putting the DBA Out of Work
One of the stated goals of SimpleDB is allowing customers to
outsource the time and effort associated with managing a web-scale database.
Managing the database is traditionally the world of the DBA. Some people have
assumed that advocating the use of SimpleDB amounts to advocating a world where
the DBA diminishes in importance. However, this is not the case at all.
One of the things that have come about from the widespread
popularity of EC2 has been a change in the role of system administrators. What
we have found is that managing EC2 virtual instances is less work than managing
a physical server instance. However, the result has not been a rash of system
administrator firings. Instead, the result has been that system administrators
are able to become more productive by managing larger numbers of servers than
they otherwise could. The ease of acquisition and the low cost to acquire and
release the computing power have led, in many cases, to a greater and more
dynamic use of the servers. In other words, organizations are using more server
instances because the various levels of the organization can handle it, from a
cost, risk, and labor standpoint.
SimpleDB and its cohorts seem to facilitate a similar change
but on a smaller scale. First, SimpleDB has less general applicability than
EC2. It is a suitable solution for a much smaller set of problems. AWS fully
advocates the use of existing relational database products. SimpleDB is an
additional option, not a replacement. Moreover, SimpleDB finds good usage in
some areas where a relational database might not normally be used, as in the
case of storing web user session data. In addition, for those projects that
choose to use SimpleDB instead of, or along with, a relational database, it does
not mean that there is no role for the DBA. Some tasks remain similar to EC2,
which can result in a greater capacity for IT departments to create solutions.
Dodging Copies of C.J. Date
There are database purists who wholeheartedly try to
dissuade people from using any type of non-relational database on principle
alone. Not only that, but they also go to great lengths to advocate the proper
use of relational databases and lament the fact that no current database
products correctly implement the relational model. Having found the one-true
data storage paradigm, they believe that the relational model is right and is
the only one that will last. The purists are not wrong in their appreciation
for the relational model and for SQL. The relational model is the cornerstone
of the database field, and more than that, an invaluable contribution to the
world of computing. It is one of the two best things to come out of 1969.
Invented by a mathematician and considered a branch of mathematics itself,
there is a solid theoretical rigor that underlies its principles. Even though
it is not a complete or finished branch, the work to date has been sound.
The world of mathematics and academic research is an
interesting place. When you have spent large quantities of your life and career
there, you are highly qualified to make authoritative comments on topics like
correctness and provability. Nevertheless, being either a relational model
expert or merely someone who holds them in high regard does not say anything
about your ability to deliver value to users. It is clearly true that modeling
your data correctly can provide measurable benefits and that making mistakes
in your model can lead to certain classes of problems. However, you can still
provide significant user value with a flawed model, and correctness is no
guarantee of success.
It is like perfectly generated XHTML that always validates. It
is like programming with a functional style (in any programming language) that
lets you prove your programs are correct. It is like maintaining unit tests
that provide 100% test coverage for every line of code you write. There is
nothing inherently bad you can say about these things. In fact, there are
plenty of good things to say about them. The problem is not a technical
problemit is a people problem. The problem is when people become hyper-focused
on narrow technological aspects to the exclusion of the broader issues of the
The people conducting database research and the ones who take
the time to help educate the computing industry deserve our respect. If you
have a degree in computer science, chances are you studied C.J. Dates work in
your database class. Among professional programmers, there is no good excuse
for not knowing data and relational fundamentals. However, the person in the
next row of cubicles who is only contributing condescending criticism to your
project is no C.J. Date. In addition, the user with 50 times your
stackoverflow.com reputation who ridicules the premise of your questions
without providing useful suggestions is no E.F. Codd. Understanding the theory
is of great importance. Knowing how to deliver value to your users is of
greater importance. In the end, avoid vociferous ignorance and dont let anyone
kick copies of C.J. Date in your face.
Other Pieces of the Puzzle
In the world of cloud computing, there are a growing number
of companies and services from which to choose. Each service provider seeks to
align its offerings with a broader strategy. With Amazon, that strategy
includes providing very basic infrastructure building blocks for users to
assemble customized solutions. AWS tries to get you to use more than one
service offering by making the different services useful with each other and by
offering fast and free data transfer between services in the same region. This
section describes three other Amazon Web Services, along with some ways you
might find them to be useful in conjunction with SimpleDB.
Adding Compute Power with Amazon EC2
AWS sells computing power by the hour via the Amazon Elastic
Compute Cloud (Amazon EC2). This computing power takes the form of virtual
server instances running on top of physical servers within Amazon data centers.
These server instances come in varying amounts of processor horsepower and
memory, depending on your needs and budget. What makes this compute cloud
elastic is the fact that users can start up, and shut down, dozens of virtual
instances at a moments notice.
These general-purpose servers can fulfill the role of just
about any server. Some of the popular choices include web server, database
server, batch-processing server, and media server. The use of EC2 can result in
a large reduction in ongoing infrastructure maintenance when compared to
managing private in-house servers. Another big benefit is the elimination of
up-front capital expenditures on hardware in favor of paying for only the
compute power that is used.
The sweet spot between SimpleDB and EC2 comes for high-data
bandwidth applications. For those apps that need fast access to high volumes of
data in SimpleDB, EC2 is the platform of choice. The free same region data
transfer can add up to a sizable cost savings for large data sets, but the
biggest win comes from the consistently low latency. AWS does not guarantee any
particular latency numbers but typically, round-tripping times are in the
neighborhood of 2 to 7 milliseconds between EC2 instances and SimpleDB in the
same region. These numbers are on par with the latencies others have reported
between EC2 instances. For contrast, additional latencies of 50 to 200
milliseconds or more are common when using SimpleDB across the open Internet.
When you need fast SimpleDB, EC2 has a lot to offer.
Storing Large Objects with Amazon S3
Amazon Simple Storage Service (Amazon S3) is a web service
that enables you to store an unlimited number of files and charges you (low)
fees for the actual storage space you use and the data transfer you use. As you
might expect, data transfer between S3 and other Amazon Web Services is fast
and free. S3 is easy to understand, easy to use, and has a multitude of great
uses. You can keep the files you store in S3 private, but you can also make
them publicly available from the web. Many websites are using S3 as a
media-hosting service to reduce the load on web servers.
EC2 virtual machine images are stored and loaded from S3. EC2
copies storage volumes to and loads storage volumes from S3. The Amazon
CloudFront content delivery network can serve frequently accessed web files in
S3. The Amazon Elastic MapReduce service runs MapReduce jobs stored in S3.
Publicly visible files in S3 can be served up via the BitTorrent peer-to-peer
protocol. The list of uses goes on and on.... S3 is really a common denominator
SimpleDB users can also find good uses for S3. Because of the
high speed within the Amazon cloud, S3 is an obvious storage location choice
for SimpleDB import and export data. It is also a solid location to place
SimpleDB backup files.
Queuing Up Tasks with Amazon SQS
Amazon Simple Queue Service (Amazon SQS) is a web service
that reliably stores messages between distributed computers. Placing a robust
queue between the computers
allows them to work independently. It also opens the door to dynamically
scaling the number of machines that push messages and the number that retrieve
Although there is no direct connection between SQS and
SimpleDB, SQS does have some complementary features that can be useful in
SimpleDB-based applications. The semantics of reliable messaging can make it
easier to coordinate multiple concurrent clients than when using SimpleDB
alone. In cases where there are multiple SimpleDB clients, you can coordinate
clients using a reliable SQS queue. For example, you might have multiple
servers that are encoding video files and storing information about those
videos in SimpleDB. SimpleDB makes a great place to store that data, but it
could be cumbersome for use in telling each server which file to process next.
The reliable message delivery of SQS would be much more appropriate for that
Comparing SimpleDB to Other Products and Services
Numerous new types of products and services are now
available or will soon be available in the database/data service space. Some of
these are similar to SimpleDB, and others are tangential. A few of them are
listed here, along with a brief description and comparison to SimpleDB.
Windows Azure Platform
The Windows Azure Platform is Microsofts entry into the cloud-computing
fray. Azure defines a raft of service offerings that includes virtual computing,
cloud storage, and reliable message queuing. Most of these services are counterparts
to Amazon services. At the time of this writing, the Azure services are available
as a Community Technology Preview. To date, Microsoft has been struggling to gain
its footing in the cloud services arena.
There have been numerous, somewhat
confusing, changes in product direction and product naming. Although Microsofts
cloud platform has been lagging behind AWS a bit, it seems that customer feedback
is driving the recent Azure changes. There is every reason to suspect that once
Azure becomes generally available, it will be a solid alternative to AWS.
Among the services falling under
the Azure umbrella, there is one (currently) named Windows Azure Table. Azure Table
is a distributed key-value store with explicit support for partitioning across storage
nodes. It is designed for scalability and is in many ways similar to SimpleDB. The
following is a list of similarities between Azure Table and SimpleDB:
access to the service is in the form of web requests. As a result, any
programming language can be used.
- Requests are
authenticated with encrypted signatures.
- Consistency is
loosened to some degree.
- Unique primary
keys are required for each data entity.
- Data within each
entity is stored as a set of properties, each of which is a name-value pair.
- There is a limit
of 256 properties per entity.
- A flexible
schema allows different entities to have different properties.
- There is a limit
on how much data can be stored in each entity.
- The number of
entities you can get back from a query is limited and a query continuation
token must be used to get the next page of results.
versioning is in place so older versions of the service API can still be used
after new versions are rolled out.
is achieved through the horizontal partitioning of data.
There are also differences between
the services, as listed here:
Table uses a composite key comprised of a partition key followed by a row key,
whereas SimpleDB uses a single item name.
- Azure Table
keeps all data with the same partition key on a single storage node. Entities
with different partition keys may be automatically spread across hundreds of
storage nodes to achieve scalability. With SimpleDB, items must be explicitly
placed into multiple domains to get horizontal scaling.
- The only index
in Azure Table is based on the composite key. Any properties you want to query
or sort must be included as part of the partition key or row key. In contrast,
SimpleDB creates an index for each attribute name, and a SQL-like query
language allows query and sort on any attribute.
- To resolve
conflicts resulting from concurrent updates with Azure Table, you have a choice
of either last-write-wins or resolving on the client. With SimpleDB,
last-write-wins is the only option.
are supported in Azure Table at the entity level as well as for entity groups
with the same partition key. SimpleDB applies updates atomically only within
the scope of a single item.
Windows Azure Table overall is very SimpleDB-like, with some
significant differences in the scalability approach. Neither service has
reached maturity yet, so we may still see enhancements aimed at easing the
transition from relational databases.
It is worth noting that Microsoft also has another database
service in the Windows Azure fold. Microsoft SQL Azure is a cloud database
service with full replication across physical servers, transparent automated
backups, and support for the full relational data model. This technology is
based on SQL Server, and it includes support for T-SQL, stored procedures,
views, and indexes. This service is intended to enable direct porting of
existing SQL-based applications to the Microsoft cloud.
Google App Engine
App Engine is a service offered by Google that lets you run
web applications, written in Java or Python, on Googles infrastructure. As an
application-hosting platform, App Engine includes many non-database functions,
but the App Engine data store has similarities to SimpleDB. The non-database
functions include a number of different services, all of which are available
via API calls. The APIs include service calls to Memcached, email, XMPP, and
App Engine includes an API for data storage based on Google Big
Table and in some ways is comparable to SimpleDB. Although Big Table is not
directly accessible to App Engine applications, there is support in the data
store API for a number of features not available in SimpleDB. These features
include data relations, object mapping, transactions, and a user-defined index
for each query.
App Engine also has a number of restrictions, some of which are
similar to SimpleDB restrictions, like query run time. By default, the App
Engine data store is strongly consistent. Once a transaction commits, all
subsequent reads will reflect the changes in that transaction. It also means
that if the primary storage node you are using goes down, App Engine will fail
any update attempts you make until a suitable replacement takes over. To
alleviate this issue, App Engine has recently added support for the same type
of eventual consistency that SimpleDB has had all along. This move in the
direction of SimpleDB gives App Engine apps the same ability as SimpleDB apps
to run with strong consistency with option to fall back on eventual consistency
to continue with a degraded level of service.
Apache CouchDB is a document database where a self-contained
document with metadata is the basic unit of data. CouchDB documents, like
SimpleDB items, consist of a group of named fields. Each document has a unique
ID in the same way that each SimpleDB item has a unique item name. CouchDB does
not use a schema to define or validate documents. Different types of documents
can be stored in the same database. For querying, CouchDB uses a system of
documents is similar to SimpleDB data but does not place limits on the amount
of data you can store in each document or on the size of the data fields.
CouchDB is an open-source product that you install and manage
yourself. It allows distributed replication among peer servers and has full
support for robust clustering. CouchDB was designed from the start to handle
high levels of concurrency and to maintain high levels of availability. It
seeks to solve many of the same problems as SimpleDB, but from the standpoint
of an open-source product offering rather than a pay-as-you-go service.
Amazon Dynamo is a data store used internally within Amazon
that is not available to the public. Amazon has published information about
Dynamo that includes design goals, run-time characteristics, and examples of
how it is used. From the published information, we know that SimpleDB has some
things in common with Dynamo, most notably the eventual consistency.
Since the publication of Dynamo information, a number of
distributed key-value stores have been developed that are in the same vein as
Dynamo. Three open-source products that fit into this category are Project
Voldemort, Dynomite, and Cassandra. Each of these projects takes a different
approach to the technology, but when you compare them to SimpleDB, they
generally fall into the same category. They give you a chance to have highly
available key-value access distributed across machines. You get more control
over the servers and the implementation that comes with the maintenance cost of
managing the setup and the machines. If you are looking for something in this
class of data storage, SimpleDB is a likely touch-free hosted option, and these
projects are hands-on self-hosted alternatives.
Compelling Use Cases for SimpleDB
SimpleDB is not a replacement for relational databases. You
need to give careful consideration to the type of data storage solution that is
appropriate for a given application. This section includes a discussion of some
of the use cases that match up well with SimpleDB.
Web Services for Connected Systems
IT departments in the enterprise are tasked with delivering
business value and support in an efficient way. In recent years, there has been
movement toward both service orientation and cloud computing. One of the
driving forces behind service orientation is a desire to make more effective
use of existing applications. Simple Object Access Protocol (SOAP) has emerged
as an important standard for message passing between these connected systems as
a means of enabling forward compatibility. For new services deployed in the
cloud, SimpleDB is a compelling data storage option.
Data transfer between EC2 instances and the SimpleDB endpoint
in the same region is fast and free. The consistent speed and high availability
of SimpleDB are helpful when defining a Service Level Agreement (SLA) between
IT and business units. All this meshes with the ability of EC2 to scale out
additional instances on demand.
There are applications in the enterprise and on the open web
that do not see a consistent heavy load. They can be low usage in general with
periodic or seasonal spikesfor instance, at the end of the month or during the
holidays. Sometimes there are few users at all times by design or simply by
lack of popularity.
For these types of applications, it can be difficult to justify
an entire database server for the one application. The typical answer in
organizations with sufficient infrastructure is to host multiple databases on
the same server. This can work well but may not be an option for small
organizations or for individuals. Shared database hosting is available from
hosting companies, but service levels are notoriously unpredictable. With
SimpleDB, low-usage applications can run within the free tier of service while
maintaining the ability to scale up to large request volumes when necessary.
This can be an attractive option even when database-sharing options are
Clustered Databases Without the Time Sink
Clustering databases for scalability or for availability is
no easy task. If you already have the heavy data access load or if you have the
quantifiable need for uptime, it is obviously a task worth taking on. Moreover,
if you already have the expertise to deploy and manage clusters of replicated
databases, SimpleDB may not be something you need. However, if you do have the
experience, you know many other things as well: you know the cost to roll the
clusters into production, to roll out schema updates, and to handle outages.
This information can actually make it easier to decide whether new applications
will provide enough revenue or business value to merit the time and cost. You
also have a great knowledge base to make comparisons between in-house solutions
and SimpleDB for the features it provides.
You may have a real need for scalability or uptime but not the
expertise. In this case, SimpleDB can enable you to outsource the potentially
expensive ongoing database maintenance costs.
Dynamic Data Application
Rigid and highly structured data models serve as the
foundation of many applications, while others need to be more dynamic. It is
becoming much more important for new applications to include some sort of
social component than it was in the past. Along with these social aspects,
there are requirements to support various types of user input and
customization, like tagging, voting, and sharing. Many types of social
applications require community building, and can benefit from a platform, which
allows data to be stored in new ways, without breaking the old data.
Customer-facing applications, even those without a social component, need to be
attentive to user feedback.
Whether it is dynamic data coming from users or dynamic changes
made in response to user feedback, a flexible data store can enable faster
Amazon S3 Content Search
Amazon S3 has become a popular solution for storing
web-accessible media files. Applications that deal with audio, video, or images
can access the media files from EC2 with no transfer costs and allow end users
to download or stream them on a large scale without needing to handle the
additional load. When there are a large number of files in S3, and there is a
need to search the content along various attributes, SimpleDB can be an
It is easy to store attributes in SimpleDB, along with pointers
to where the media is stored in S3. SimpleDB creates an index for every
attribute for quick searching. Different file types can have different
attributes in the same SimpleDB domain. New file types or new attributes on
existing file types can be added at any time without requiring existing records
to be updated.
Empowering the Power Users
For a long time, databases have been just beyond the edge of
what highly technical users can effectively reach. Many business analysts,
managers, and information workers have technical aptitude but not the skills of
a developer or DBA. These power users make use of tools like spreadsheet
software and desktop databases to solve problems. Unfortunately, these tools
work best on a single workstation, and attempts at sharing or concurrent use
frequently cause difficulty and frustration; enterprise-capable database
software requires a level of expertise and time commitment beyond what these
users are willing to spend.
The flexibility and scalability of SimpleDB can be a great boon
to a new class of applications designed for power users. SimpleDB itself still
requires programming on the client and is not itself directly usable by power
users. However, the ability to store data directly without a predefined schema
and create queries is an enabling feature. For applications that seek to
empower the power users, by creating simple, open-ended applications with
dynamic capabilities, SimpleDB can make a great back end.
Existing AWS Customers
This chapter pointed out earlier the benefits of using EC2
for high-bandwidth applications. However, if you are already using one or more
of the Amazon Web Services, SimpleDB can be a strong candidate for queryable
data storage across a wide range of applications. Of course, running a
relational database on an EC2 instance is also a viable and popular choice.
Moreover, you would do well to consider both options. SimpleDB requires you to
make certain trade-offs, but if the choices provide a net benefit to your
application, you will have gained some great features from AWS that are
difficult and time consuming to develop on your own.
Amazon SimpleDB is a web service that enables you to store
semi-structured data within Amazons data centers. The service provides
automatic, geographically diverse data replication and internal routing around
failed storage nodes. It offers high availability and enables horizontal
scalability. The service allows you to offload hardware maintenance and
database management tasks.
You can use SimpleDB as a distributed key-value store using the GetAttributes, PutAttributes, and DeleteAttributes API calls.
You also have the option to query for your data along any of its attributes
using the Select API call. SimpleDB is not a relational database, so there are
no joins, foreign keys, schema definitions, or relational constraints that you
can specify. SimpleDB also has limited support for transactions, and updates
propagate between replicas in the background. SimpleDB supports strong
consistency, where read operations immediately reflect the results of all
completed and eventual consistency, where storage nodes are updated
asynchronously in the background.
The normal window of time for all storage nodes to reach
consistency in the background is typically small. During a server or network
failure, consistency may not be reached for longer periods of time, but eventually
all updates will propagate. SimpleDB is best
used by applications able to deal with eventual consistency and benefit from
the ability to remain available in the midst of a failure.
Hands-on Tutorial for Getting Started with Amazon SimpleDB
Amazon Web Services: A Developer Primer