Biographical Information
Guy Harrison
Director of Research and Development at Quest Software
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Guy Harrison is a director of research and development at Quest Software, and has over 20 years' experience in application and database administration, performance tuning and software development. He is the author of Oracle Performance Survival Guide (Prentice Hall, 2009) and MySQL Stored Procedure Programming (O'Reilly with Steven Feuerstein), as well as other books, articles and presentations on database technology. Harrison is the architect of Quest's Spotlight family of diagnostic products and has contributed to the development of other Quest products, including Toad. He can be found on the internet at www.guyharrison.net, on Twitter @guyharrison, or email him at guy.harrison@quest.com.
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Both open source software ( OSS) and cloud computing continue to experience strong interest and growth despite the economic downturn. Clearly, both provide the promise of reduced operating and software licensing costs. For instance, corporations looking to reduce the cost incurred by Microsoft Office licensing are looking more closely at the open source OpenOffice alternative, or at Google's online application suite, Google Apps. There's understandable resistance to moving from the rich experience offered by Microsoft to these lower-cost alternatives, but resistance has a way of disappearing in the face of financial imperatives.
The business intelligence (BI) market is big: at least $10 billion in 2008 and much more if you include data warehousing projects. The tough economic environment may slow the growth of the BI market, but cost constraints, compliance and similar measures demanded by the current economy require accurate and timely business data, so BI is expected to remain a vigorous market segment regardless of the macro-economic situation.
Way back in 2003, Walmart announced that it would require Radio Frequency ID (RFID) tags—so-called "electronic barcodes"—to be attached to virtually all merchandise. Walmart pioneered the use of the printed bar code back in the 1970s, and many—myself included—became convinced that the company's directive would be the tipping point leading to universal adoption of RFID tabs in consumer goods and elsewhere.
Predictive Analytics - sometimes referred to as Predictive Data Mining - is a branch of Business Intelligence that attempts to use historical data to make predictions about future events. At its simplest, predictive analytics utilizes statistical techniques, such as correlation and regression, which many of us have encountered in college or even high school. Correlation analysis determines if there is a statistically significant relationship between two variables. For instance, height and age are highly correlated, while IQ and height are very weakly correlated. Regression attempts to find an equation between the two or more variables, so that you can predict one from the other.
Virtualization has changed the IT landscape more dramatically than perhaps any other technology introduced over the past decade. Virtualized environments are omnipresent in the modern data center due to their economic advantages in hardware consolidation and manageability.
Both open source software (OSS) and cloud computing continue to experience strong interest and growth despite the economic downturn. Clearly, both provide the promise of reduced operating and software licensing costs.
few years ago, it seemed as though the days of the "micro-ISV"-very small Independent software vendors consisting of one or two developers-were over. The role once played by shareware windows applications had been supplanted by free web applications financed by advertising revenue. The start-up costs for such web applications-including funding a scalable and reliable web hosting infrastructure-were beyond the reach of most small software entrepreneurs.
Non-relational cloud databases such as Google's BigTable, Amazon's SimpleDB and Microsoft'sSQL Server Data Services (SSDS) have emerged. But while these new data stores may well fill a niche in cloud-based applications, they lack most of the features demanded by enterprise applications - in particular, transactional support and business intelligence capabilities.
For the first time in over 20 years, there appear to be cracks forming in the relational model's dominance of the database management systems market. The relational database management system (RDBMS) of today is increasingly being seen as an obstacle to the IT architectures of tomorrow, and - for the first time - credible alternatives to the relational database are emerging. While it would be reckless to predict the demise of the relational database as a critical component of IT architectures, it is certainly feasible to imagine the relational database as just one of several choices for data storage in next-generation applications.
In the classic comedy, "The Hitchhikers' Guide to the Galaxy," a frustrated Ford Prefect can't understand why a bunch of marketing consultants shipwrecked on prehistoric earth can't invent the wheel.
MOORE'S law—first expressed by Intel cofounder Gordon Moore in 1965—predicts that computing power will increase exponentially, doubling roughly every 18 months. Moore's law has proved remarkably accurate and we have all benefited from the rapid growth in CPU and computer memory available for our desktop computers.
Until recently, IT professionals have been conditioned to regard response time, or throughput, as the ultimate measure of application performance. It's as though we were building automobiles and only concerned with faster cars and bigger trucks. Yet, just as the automotive industry has come under increasing pressure to develop more fuel-efficient vehicles, so has the IT industry been challenged to reduce the power drain associated with today's data centers.
Spreadsheets, which have long been a disruptive force to enterprise IT, to some extent are the "killer" applications that helped drive the adoption of personal computers (PCs) in the enterprise. Spreadsheet products such as Lotus 1,2,3 - and early versions of Excel on the Mac - saw rapid adoption by business users. Inevitably, these users pushed the boundaries of the spreadsheet model, using spreadsheets as databases, and even to develop simple business applications. In the late 1980s, it was typical to see corporate IT rolling out massively expensive mainframe-based solutions, while departmental users got their real work done on spreadsheets running on cheap PCs.
Open source applications were somewhat niche at the beginning of the decade but now are clearly mainstream. Credible open source alternatives now exist for almost every category of application, as well as every component of the application.
NoSQL - probably the hottest term in database technology today - was unheard of only a year ago. And yet, today, there are literally dozens of database systems described as "NoSQL." How did all of this happen so quickly? Although the term "NoSQL" is barely a year old, in reality, most of the databases described as NoSQL have been around a lot longer than the term itself. Many databases described as NoSQL arose over the past few years as reactions to strains placed on traditional relational databases by two other significant trends affecting our industry: big data and cloud computing.
In biology, we are taught that survival favors diversity. Organisms that reproduce without variation die out during periods of rapid change, while organisms that show variation in feature tend to survive and adapt. Likewise, ecosystems consisting of relatively few homogenous species thrive only when conditions stay static. Does IT diversity create a competitive advantage in the business application ecosystem? Predictably, large vendors with vertically integrated stacks argue that mixing software components is a Bad Thing. These vendors claim that reducing the diversity in the application stack leads to better efficiency and maintainability.
Although VMware continues to hold the majority share of the commercial virtualization market, other virtualization technologies are increasingly significant, though not necessarily as high profile. Operating system virtualization-sometimes called partial virtualization-allows an operating system such as Solaris to run multiple partitions, each of which appears to contain a distinct running instance of the same operating system. However, these technologies cannot be used to host different operating system versions, making them less appealing to enterprises seeking to consolidate workloads using virtualization.
In 1995, Netscape founder Marc Andreessen famously claimed that applications of the future would run within a web browser, relegating the role of the operating system - Windows, in particular - to "a poorly debugged set of device drivers." Fifteen years later, we can see that although rich applications such as Microsoft Office are still dominant, the web browser has become a platform that can deliver almost any conceivable type of business or consumer application.
The idea of "virtual" reality—immersive computer simulations almost indistinguishable from reality—has been a mainstay of modern "cyberpunk" science fiction since the early 1980s, popularized in movies such as The Thirteenth Floor and The Matrix. Typically, a virtual reality environment produces computer simulated sensory inputs which include at least sight and sound, and, perhaps, touch, taste and smell. These inputs are presented to the user through goggles, earphones and gloves or—in the true cyberpunk sci-fi—via direct brain interfaces.
Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to maintaining Google's website indexes.
Attendees at the O'Reilly Velocity conference in June were treated to the unusual phenomenon of a joint presentation by Google and Microsoft. The presentation outlined the results of studies by the two companies on the effects of search response time. Aside from the novelty of Microsoft-Google cooperation, the presentation was notable both in terms of its conclusions and its methodology.
Google's first "secret sauce" for web search was the innovative PageRank link analysis algorithm which successfully identifies the most relevant pages matching a search term. Google's superior search results were a huge factor in their early success. However, Google could never have achieved their current market dominance without an ability to reliably and quickly return those results. From the beginning, Google needed to handle volumes of data that exceeded the capabilities of existing commercial technologies. Instead, Google leveraged clusters of inexpensive commodity hardware, and created their own software frameworks to sift and index the data. Over time, these techniques evolved into the MapReduce algorithm. MapReduce allows data stored on a distributed file system - such as the Google File System (GFS) - to be processed in parallel by hundreds of thousands of inexpensive computers. Using MapReduce, Google is able to process more than a petabyte (one million GB) of new web data every hour.
When a company like Microsoft talks about the future of computing, you can expect a fair bit of self-serving market positioning - public software companies need to be careful to sell a vision of the future that doesn't jeopardize today's revenue streams. But, when a company like Microsoft releases a new version of its fundamental development framework - .NET, in this case - you can see more clearly the company's technical vision for the future of computing.
There's an old but clever internet parody describing the "Built-in Orderly Organized Knowledge device (BOOK)." This device is described as a "revolutionary breakthrough in technology" that is compact and portable, never crashes and supports both sequential and indexed information access. Though satirical, the article makes excellent points: the printed book is indeed an information technology device, arguably the oldest in widespread use today