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Copy, Paste, Cloud

One of my favorite features of EC2 is the ability to create virtual machine templates and re-use them to create fresh copies of a virtual machine. This is great but things rapidly get onerous when you’re trying to duplicate infrastructure.

Amazon recently unveiled a new service called AWS CloudFormation. There are currently many Amazon cloud offerings available: S3, Elastic Block Storage, EC2, and Elastic Beanstalk are just a few. AWS CloudFormation is more than just another member of the family: it ties them all together.

The idea behind AWS CloudFormation is to make it easy to create a collection of AWS resources and then deploy them the same way every time. AWS CloudFormation is similar to using Chef recipes to deploy software configuration. In this case we’re deploying an entire infrastructure stack to multiple virtual machines via a recipe. We can design our infrastructure on AWS. As our business grows we will be able to quickly and easily duplicate crucial parts of our infrastructure.

AWS CloudFormation makes it simpler to manage all of your infrastructure. Deployments of new infrastructure become a matter of pushing out a template. If there are problems with a deployment, the changes can be rolled back and a clean up happens to make sure you aren’t charged for anything that you’re not using.


In a traditional IT department, there is a design, purchase, deploy cycle that can potentially take a very long time. In previous jobs, we’ve had to design the infrastructure based on obscure internal capacity planning metrics. Once we’d made predictions/guesses about our future growth, we would then wait for weeks or even months to acquire new hardware. Once we had the hardware, it might even sit around for days or weeks before we were finally able to provision, configure, and deploy the servers on the network. That doesn’t even include deploying our own software on the server.

On the flip side of that coin, by combining AWS CloudFormation plus Chef/Puppet, we can now push a new batch of servers out into the cloud in a matter of minutes and have them running in a few hours. Our software can be automatically installed and configured with Chef or Puppet. While we still need to write templates, once we’ve created and tested our templates for specific purposes (blog, database, community site, whatever), we’re able to fully automate deployments.

Scaling Out

AWS CloudFormation can also ease the pain of scaling out our applications.

Typically when we scale out an application, we’re starting from a monolithic application stack. All of the assets in our stack have been scaled up to a point where it’s cost prohibitive to keep scaling. At this point, we’d examine each layer of our application and determine the best place to add caching or scale out to use multiple application or database servers. As we keep scaling our stack, we need to add more load balancers, caching servers, and database read slaves until we’ve exhausted our options and have to revisit our application design.

Rather than engaging in the exercise of attempting to scale all of our customers at once, why don’t we start out by sharding all application resources at the customer level? While this increases the overall cost of operating our business, it makes it easy to scale elastically in response to a changing customer base. The busiest customers will get larger servers and increased performance that meets their needs. It also becomes possible to locate our data close to your customer in one of several Amazon zones.

For businesses offering software as a service, this makes a great deal of sense. They get an easy way to monitor usage per customer and can scale appropriately within known guidelines and with well known costs.

Wrap Up

AWS CloudFormation makes it possible to provision and deploy infrastructure using a set of templates. When you combine CloudFormation with Chef or Puppet, it becomes very easy to deploy infrastructure and then deploy additional configuration changes on top of the infrastructure. Ultimately, AWS CloudFormation makes it easy to quickly and easily deploy new infrastructure in response to changes in load or customer demand.

If you’re interested in some of the discussion around AWS CloudFormation, be sure to check out the Hacker News thread on the subject.

Introduction to Riak … TONIGHT!

I’ll be speaking at the Columbus Ruby Brigade and giving an introduction to Riak tonight at 6:30PM!

There will be pizza and soda and Ruby and me. You can even stick around afterwards while we all go next door for drinks (you can buy my Diet Cokes all night if you really like the presentation).

Riak: An Overview

This presentation will lead you through an overview of Riak: a flexible, decentralized key-value store. Riak was designed to provide a friendly HTTP/JSON interface and provide a database that’s well suited for reliable web applications.

Add it to your calendar!

Protecting Your Content – Copyright, Licensing, and You

Why Should I Worry About Licensing?

You probably just have a blog, or maybe you haven’t even started blogging yet. Maybe you’re just sharing your thoughts on Facebook Notes or Google Pages. However you look at it you’re probably certain that you don’t need to worry about your writing on the web. It is, after all, your content.

Think again.

In all fairness, Facebook’s terms of use are some of the more consumer friendly terms of service out there. Facebook does not claim copyright over your content, but using Facebook immediately grants Facebook “a non-exclusive, transferable, sub-licensable, royalty-free, worldwide license to use any IP content that you post on or in connection with Facebook (‘IP License’)”. Basically, Facebook can use any picture or thought you’ve posted at any time with no notice to you. Their ability to use your content continues as long as you have an account and you have not shared your content with anyone.

Google’s terms of service are not as friendly as Facebook’s. To start with, Google’s terms use legal language while Facebook’s terms are in something reasonably close to plain English. Google’s terms get worse from there. Instead of allowing you to remove your content by permanently deleting it (and all copies), Google’s terms state that you’re giving them the right to use your thoughts until the end of time, or until you stop using all of Google’s services (see sections 11 and 13.2). Both companies’ terms of service contain my favorite legal provision: the terms are subject to change at any time. In short, if you aren’t hosting your own content, you don’t own it. Not completely. You can claim you’re copyrighting it, but someone else can use it because you’ve implicitly given them permission, and that permission may change.

Back to my earlier question: why should you worry about licensing? You should worry about licensing because you want to be able to control your own content. There’s nothing that stops a third party from changing the terms of service to require their permission if you republish something. If you wanted to republish a blog post on another site, syndicate your content, or print something you wrote in a book you could suddenly find yourself in a legal mess. What if you don’t want pictures of yourself, your friends, or your children to appear in ads?

Licensing comes down to control over your content and maintaining that control into the future. If you want to keep control, you need to examine the license that you have chosen for your content. This doesn’t just apply to the written word, it applies to your presentations, your photographs, and your code samples.

Written Licensing

What’s the best way to protect content you’ve written? That all depends on how you want people to be able to use and re-use your content.

The Well Worn Path: Copyrighting Your Work

The strictest way to protect your content is to copyright it. Stanford University have compiled a great list of copyright resources and it’s important to understand the rights around your work. A copyrighted work doesn’t need to be marked as such, but it will make it much easier to enforce your copyright. Very few people actively want to steal your work, by including a copyright notice with contact information you are making it easier for other authors to track you down and get your permission to use part of your work. The best part is that because of international treaties, there is very little difference in copyright laws between different countries.

Keep in mind that copyrighting your work does not prevent others from reusing portions of your work under fair use principles. Fair use is a tricky thing and is subject to some vague criteria. If you aren’t competing with the author, copying wholesale, building a new work, and are not motivated by a desire for commercial gain, you’re on the way to falling under fair use rules. When in doubt, ask the original author for permission. If you can’t find the original author, find an attorney.

While there are some nuances to copyright law, it is fairly straightforward. You mark your work as copyrighted and that’s it. Others can make use of portions of your work under fair use guidelines and they should ask for permission, but it isn’t strictly necessary.

Flexible Designs for the Future: Creative Commons

A Creative Commons license is, on the surface, not so different from traditional copyright. It’s a more flexible copyright. Rather than have a single, restrictive agreement between the copyright holder and the rest of the world, the Creative Commons license makes it easy for copyright holders to expressly allow certain behaviors.

It all boils down to a few questions:

  • Do you want to allow commercial use of your work?
  • Do you want to allow adaptations of your work?
  • Do you want the terms of the license to continue?

Saying “no” to any of these questions doesn’t prevent anyone from using your work in those ways, they just need to obtain your express permission. A Creative Commons license page clearly explains the terms of a particular license making it very easy for readers and other authors to learn how they can or cannot use your work.

One of the most important aspects of the Creative Commons license is the ability to require future authors to share alike. Adding the share alike provision to your Creative Commons license requires future collaborators to distribute their derivative work under the same license; your work and all work that builds on it will always be available under the same terms you envisioned when you created the content.

Learn more.

The Public Domain

I’ll admit it freely: when I started writing this, I didn’t know a whole lot about how the public domain worked and what it meant. I knew that everything in the public domain was free and couldn’t be taken under someone else’s control, but I didn’t know much more than that.

A work enters the public domain when the intellectual property rights on the work expire or when those rights are forfeited. Basically, I can take anything I’ve previously written and decree that my work is now in the public domain. It belongs to everyone at that point. Work that has entered the public domain is free for anyone else to build upon. In many ways, the public domain is crucial for the advancement of science and the arts. It makes it possible to build on earlier works, to examine and expand upon the work of Isaac Newton or to re-arrange a symphony to be performed by kazoos and barking dogs. Works in the public domain carry no restrictions on their use.

Unfortunately, the definition of public domain varies from country to country so there’s no reliable guarantee or best guess that you can make about how something can be used or re-used, even if the author states their work is in the public domain. When in doubt, consult an attorney (or Google).

The biggest thing to remember about putting your own work in the public domain is that it’s out there for anyone to use and re-use. A less scrupulous person could collect your blog posts and arrange them into a coherent narrative and the publish it as a book. They could also make as many changes as they wanted and there would be nothing you could do to correct the situation.

Software Licensing

Why should we even be talking about software licensing? Software licensing is important if you want to release software for people to use, or even if you want to put sample code on your blog for others to re-use. Of course, you could state in your blog’s copyright that all of your source code is covered under the same restrictive copyright as the rest of your blog, but where’s the fun in that?

Proprietary Software

This is software that is exclusively licensed by the copyright holder. The copyright holder says “here, you can use this because you gave me money, but you have to abide by these rules.” After which they drop a license document the size of a phone book on your desk with an invoice stapled to the top.

So it’s not really like that. How does it work?

With proprietary software, the copyright holder grants you the right to use their software within certain conditions – you can’t modify it or sell it along to your buddies or reverse engineer it to make your own version. License terms vary from vendor to vendor. Some are incredibly permissive and others are very strict. It’s important to look at your software license if you’re ever in doubt of what you can or can’t do with your software.

Likewise, if you’re going to be creating software, you need to be aware of what the terms of your license mean. Commercial software is best licensed under a proprietary license. After all, if I can download and compile your source code free of charge, why should I pay you for your software?

Open Source Software

There are some people who will take issue and say that I should call this section Free and Open Source Software (FOSS) or Free, Libre, and Open Source Software (FLOSS). To these people I say, “get your own blog!”

Open Source Software (OSS) is a contentious area of software. In practice, OSS is software that is released under a specific license and the source code is distributed with the software. In fact, OSS software usually comes as nothing but source code with a license attached. Helpful people often provide compiled versions of the software for various hardware and software platforms.

One of the greatest strengths of open source software is that future users of the software and given specific rights that are normally reserved for copyright holders. This is a lot like Creative Commons licensing in some ways. There are far too many open source licenses to examine them in any detail, so be sure to do your homework if you ever need to choose one.

Now, why should you choose an open source license? I choose to release my demo code under an open source license because I want people to be able to use it, re-use it, and feel free to contribute back. Demo code should stand on its own, but it’s important to remember that your demo code is part of your reputation – keep it safe.

Some good options for open source licenses are the Apache License, the MIT License, or the LGPL. Make sure you read the licenses and understand them before using them. Some licenses have more provisions than others, some restrict future commericial use, and some have almost no provisions at all (the MIT and BSD licenses are like this).

Public Domain

Public domain isn’t specific to the written word, art, and music – software can be covered under the public domain as well. The same legal ramifications apply to software released under the public domain. One of the more famous pieces of public domain software is SQLite.

Why Should I Be Worried About This?

Anyone worried about maintaining control of their own work should be worried about copyright and software licensing. Maintaining control of your work and how it can be distributed is an important part of producing content. If you want to be permissive about ho`w your work is used, you can grant rights to people in advance through the Creative Commons or through open source licensing. If you want people to request permission, you can use stricter copyright requirements and proprietary software licensing. There are many choices available.

Database Restores – Where’s my Transaction Log Backup?

Developers! DBAs! Has this ever happened to you?

Surprise! It's a database migration error!

You’re chugging along on a Friday night getting ready for your weekend deployment. Your 2 liter of Shasta is ice cold, you have your all Rush mix tape, and you’re wearing tube socks with khakis. Things are looking up. You open up your deployment script. You’re confident because you’ve tested it in the QA environment and everything worked. You press F5 and lean back in your chair, confident that the script is going to fly through all of the changes. Suddenly, there’s an error and you’re choking in surprise on Shasta.

In an ideal world, you could pull out your trusty log backups and do a point in time restore, right? What if you’ve never taken a transaction log backup? What if you only have full database backups? Can you still recover from this situation? The answer, thankfully, is yes.

Let’s break something!

USE ftgu;

-- at midnight, we took our initial back up
BACKUP DATABASE ftgu TO DISK = 'C:\ftgu-1.bak'

-- customer data from the business is inserted
-- more customer data is inserted

-- some kind of migration goes here

-- insert a bad value
INSERT INTO Bins (Shelf, Bin)
VALUES ('B', 9)



-- wait for a bit
WAITFOR DELAY '00:01:00';

-- do something dumb
FROM Products p
JOIN Bins b ON p.BinID = b.BinID
WHERE b.Shelf = 'B';



We have a starting backup, no t-log backups, and we’ve gone and deleted some important data from the production database. How do we get it back? If we restored the database from our first backup we might lose a lot of data. Who knows when the last database backup was taken? Oh, midnight. So, in this case, we’d lose a day of data. Well, bugger. In a panic, we save the state of our broken database.

-- ack!
BACKUP DATABASE ftgu TO DISK = 'C:\ftgu-2.bak';

And then we realize that we also need our transaction log:

-- ah crap, I need to back up my log to get point in time recovery!
TO DISK = 'C:\ftgu-log-1.trn';

Here’s the kicker – the transaction log has never been backed up. (In my experience, this is all too common.) This database has been running for a week or a year or three years without any kind of transaction log backups. We’re screwed right? I mean, wouldn’t we have to apply all of the transactions from the log to the very first full backup we have? No.

Let’s get started and restore our last good backup. We always have our backup with missing data, just in case we need it for some reason.

-- switch to master (need to make sure nobody else is using that database)
USE master;

-- restore the last full backup with known good data
-- make sure to specify NORECOVERY so we can 
-- apply our transaction log backup
FROM DISK = 'C:\ftgu-1.bak'

SQL Server is cunning and records the log sequence number (LSN) from the last full backup (technically it’s the start and end LSN from the last full backup). If we have a log backup that encompasses the relevant LSNs, we’re good to go. Since our transaction logs were never backed up before today, we’re safe.

We’re going to use something called

-- restore the log backup until right before we started
-- this is called "point in time recovery"
FROM DISK = 'C:\ftgu-log-1.trn'
WITH STOPAT = '2011-02-13 10:03:55.653';

Even though we never took a transaction log backup before today, we’re able to take a backup and recover from what initially seemed like a bad situation.

Introduction to Riak – Next Monday

I’ll be speaking at the Columbus Ruby Brigade and giving an introduction to Riak next Monday, February 21, at 6:30PM.

Riak: An Overview

This presentation will lead you through an overview of Riak: a flexible, decentralized key-value store. Riak was designed to provide a friendly HTTP/JSON interface and provide a database that’s well suited for reliable web applications.

Add it to your calendar!

SQL Saturday 60 Resources

SQL Saturday 60 was a week ago and I completely failed to post resources from the presentation in a timely manner.

The SQL Server Internals resources have been available for a while:… You just had to know to look for them.

The Modeling Muddy Data talk is available on GitHub: This presentation is released under a Creative Commons Attribution-ShareAlike license which means that we can all make things better by collaborating on the presentation materials. I’ll slowly be adding more information to the write up of the talk that is in the README.

Data Durability

A friend of mine half-jokingly says that the only reason to put data into a database is to get it back out again. In order to get data out, we need to ensure some kind of durability.

Relational databases offer single server durability through write-ahead logging and checkpoint mechanisms. These are tried and true methods of writing data to a replay log on disk as well as caching writes in memory. Whenever a checkpoint occurs, dirty data is flushed to disk. The benefit of a write ahead log is that we can always recover from a crash (so long as we have the log files, of course).

How does single server durability work with non-relational databases? Most of them don’t have write-ahead logging.

MongoDB currently has limited single server durability. While some people consider this a weakness, it has some strengths – writes complete very quickly since there is no write-ahead log that needs to immediately sync to disk. MongoDB also has the ability to create replica sets for increased durability. There is one obvious upside to replica sets – the data is in multiple places. Another advantage of replica sets is that it’s possible to use getLastError({w:...}) to request acknowledgement from multiple replica servers before a write is reported as complete to a client. Just keep in mind that getLastError is not used by default – application code will have to call the method to force the sync.

Setting a w-value for writes is something that was mentioned in Getting Faster Writes with Riak. Although, in that article we were decreasing durability to increase write performance. In Amazon Dynamo inspired systems writes are not considered complete until multiple clients have responded. The advantage is that durable replication is enforced at the database and clients have to elect to use less security for the data. Refer to the Cassandra documentation on Writes and Consistency or the Riak Replication documentation for more information on how Dynamo inspired replication works. Datastores using HDFS for storage can take advantage of HDFS’s built-in data replication.

Even HBase, a column-oriented database, uses HDFS to handle data replication. The trick is that rows may be chopped up based on columns and split into regions. Those regions are then distributed around the cluster on what are called region servers. HBase is designed for real-time read/write random-access. If we’re trying to get real-time reads and writes, we can’t expect HBase to immediately sync files to disk – there’s a commit log (RDBMS people will know this as a write-ahead log). Essentially, when a write comes in from a client, the write is first written to the commit log (which is stored using HDFS), then it’s written in memory and when the in-memory structure fills up, that structure is flushed to the filesystem. Here’s something cunning: since the commit log is being written to HDFS, it’s available in multiple places in the cluster at the same time. If one of the region servers goes down it’s easy enough to recover from – that region server’s commit log is split apart and distributed to other region servers which then take up the load of the failed region server.

There are plenty of HBase details that have been grossly oversimplified or blatantly ignored here for the sake of brevity. Additional details can be found in HBase Architecture 101 – Storage as well as this Advanced HBase presentation. As HBase is inspired by Google’s big table, additional information can be found in Chang et al. Bigtable: A distributed storage system for structured data and The Google File System.

Interestingly enough, there is a proposed feature for PostgreSQL 9.1 to add synchronous replication to PostgreSQL. Current replication in PostgreSQL is more like asynchronous database mirroring in SQL Server, or the default replica set write scenario with MongoDB. Synchronous replication makes it possible to ensure that data is being written to every node in the RDBMS cluster. Robert Haas discusses some of the pros and cons of replication in PostgreSQL in his post What Kind of Replication Do You Need?.

Microsoft’s Azure environment also has redundancy built in. Much like Hadoop, the redundancy and durability is baked into Azure at the filesystem. Building the redundancy at such a low level makes it easy for every component of the Azure environment to use it to achieve higher availability and durability. The Windows Azure Storage team have put together an excellent overview. Needless to say, Microsoft have implemented a very robust storage architecture for the Azure platform – binary data is split into chunks and spread across multiple servers. Each of those chunks is replicated so that there are three copies of the data at any given time. Future features will allow for data to be seamlessly geographically replicated.

Even SQL Azure, Microsoft’s cloud based relational database, takes advantage of this replication. In SQL Azure when a row is written in the database, the write occurs on three servers simultaneously. Clients don’t even see an operation as having committed until the filesystem has responded from all three locations. Automatic replication is designed into the framework. This prevents the loss of a single server, rack, or rack container from taking down a large number of customers. And, just like in other distributed systems, when a single node goes down, the load and data are moved to other nodes. For a local database, this kind of durability is typically only obtained using a combination of SAN technology, database replication, and database mirroring.

There is a lot of solid technology backing the Azure platform, but I suspect that part of Microsoft’s ultimate goal is to hide the complexity of configuring data durability from the user. It’s foreseeable that future upgrades will make it possible to dial up or down durability for storage.

While relational databases are finding more ways to spread load out and retain consistency, there are changes in store for MongoDB to improve single server durability. MongoDB has been highly criticized for its lack of single server durability. Until recently, the default response has been that you should take frequent backups and write to multiple replicas. This is still a good idea, but it’s promising to see that the MongoDB development team are addressing single server durability concerns.

Why is single server durability important for any database? Aside from guaranteeing that data is correct in the instance of a crash, it also makes it easier to increase adoption of a database at the department level. A durable single database server makes it easy to build an application on your desktop, deploy it to the server under your desk, and move it into the corporate data center as the application gains importance.

Logging and replication are critical technologies for databases. They guarantee data is durable and available. There are also just as many options as there are databases on the market. It’s important to understand the requirements of your application before choosing mechanisms to ensure durability and consistency across multiple servers.


Goals for 2011 – Early Update

It’s a bit early to be updating my goals for 2011, but I’m really excited about this one. Over the course of last week, I wrote an article about loading data into Riak. I had a brief conversation with Mark Phillips (blog | twitter) about adding some of the code to the Riak function contrib.

This is where a sane person would say “Yeah, sure Mark, do whatever you want with my code.” Instead I said something like “I’d be happy to share. How about I make a generic tool?” About 40 minutes later I had a working chunk of code. 30 minutes after that I had refactored the code into a driver and a library. I wrote up some documentation and sent everything off to be included in the main Riak function contrib repository. A couple of days and a documentation correction later and you can now see my first code contribution to the open source world on the internet: Importing YAML.

While I’m really excited about this, and it’s very important to me, there’s more to take away from this than just “Yay, I did something!” We’re all able to give something back to our community. In this case I took code I had written to perform benchmarks and extracted a useful piece of demonstration code from it. Share your knowledge with the world around you – it’s how we get smarter.

A Technical Plan for 2011

The Last Ten Years

My career has been particularly interesting. I’ve been very fortunate to work with a variety of different languages, platforms, databases, frameworks, and people. I started off working with Perl on HP-UX. As I started automating more of my job, I added ASP.NET to the mix. Eventually I learned about databases, first with Oracle, then SQL Server, then with PostgreSQL, and finally back to SQL Server. Along the way I’ve held job a variety of different job titles – system administrator, system engineer, developer, consultant, architect, and database administrator.

I’ve worked with a lot of different systems, architectures, and design philosophies. The one thing that’s stuck with me is that there is no one size fits all answer. That extends beyond languages and design patterns – it goes right down to the way we’re storing data. One of the most interesting things going on right now is that it’s easier than ever to pick the right tools for the job.

The Next Twelve Months

Over the next twelves months, I’m going to be digging into hybrid database solutions. Some people call it polyglot persistence. You can call it what you like, but the fact remains that it is no longer necessary to store all of our data in a relational database. Frankly, I’m encouraging people to look into ways to store their data outside of a relational database. Not because RDBMSes are bad or wrong, but because there is a lot of data that doesn’t need to be in a relational database – session data, cached data, and flexible data.

Why Focus on Hybrid Data?

The idea behind hybrid data is that we use multiple databases instead of one database. Let’s say that we have an online store where we sell musical equipment. We want to store customer data in a relational database, but where should we store the rest of our information? Conventional thinking says that we should keep storing our data in a relational database. Sessions might be stored in memory somewhere and shopping carts might get stored in the database, but they’ll end up on faster, more expensive, solid state drives.

There are other ways to store data.

Let’s think about all of this for a minute. Why do we force our databases into existing paradigms? Why aren’t we thinking about new and interesting ways to store our data?

Sessions are a great place to start. Sure, we could use something like memcached, but why not examine Redis or App Fabric Cache? Both of these databases have support for strongly typed data. They both allow the data to be persisted to disk, if needed, and they allow for data to be expired over time. This is perfect for working with any kind of cached data – it stays in a format our applications need but we can expire it or save it as needed.

The flexibility to store our data the way that applications use it is important. Session data should be rapidly accessible. Other applications don’t need to read it. It doesn’t need to be reportable. It merely needs to be fast.

Shopping carts are different. Amazon’s own use cases and needs drove the development of Dynamo to be a durable, eventually consistent, distributed key-value store. Shopping carts are write heavy environments. It’s rare that users need to view everything that’s in a shopping car, but they need to be able to review it quickly when the time comes. Likewise, when the time comes to review a shopping cart, any delay or slowdown means there’s a chance the user will simply abandon the cart. Dynamo fills these requirements quite well.

Since Dynamo is only available inside of Amazon, how are we supposed to work with it ourselves? Riak is a clone of Dynamo that meets our need for a shopping cart. It’s a key/value database; it’s fault tolerant, and it’s fast.

Why not store a shopping cart in a relational database? It is, after all, a pretty simple collection of a user identifier, an item number, an item description, price, and quantity. Shopping carts are highly transient. Once an order has been placed, the shopping cart is cleared out and the data in the cart moves into the ordering system. Most shopping carts will be active for a very short period of time – a matter of minutes at most. Over their short lives shopping carts will almost entirely be written to and only read a few times. Instead of building complex sharding mechanisms to spread load out across a number of database servers, why not use a database designed to handle large load spread across a number of servers?

Where Does This Fit Into the Enterprise?

Enterprises should be adopting these technologies as fast as they can. Not because they are replacing the relational database, but because they free the relation database from things it’s bad at and leave it to perform tasks that it excels at. Relational databases are great for core business logic – they have a lot of baked in functionality like data integrity and validation. As we’ve already discussed, relational databases are not well suited to storing highly volatile data.

By moving volatile data into better suited types of database, enterprises can increase the capacity of their database systems, provide redundancy, and increase scalability by using off the shelf solutions. The trick, of course, lies in integrating them. And that is what I’m going to be playing around with this year.

SQL Server Internals – Live at the TriPASS Live Meeting

Join me on Tuesday, January 11 at 12:00PM Eastern and take a break from your work day to learn about SQL Server Internals. There’s some information on the event page.

Add it your calendar!

SQL Server Internals

Want to know what makes SQL Server tick? Ever wonder what SQL Server is doing when you run a query? Ever wonder which parts of SQL Server are responsible for specific functionality? Want to know what a HOBT is? I can’t promise answers to every question, but I can set you on the path to knowledge about the inner workings of SQL Server.

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