Like most production systems, life happens in real time; and there has been several major paradigm shifts happening lately. It's easy to shrug AJAX off as revamped XMLHTTP from late 90's but we all know this isn't exactly the case. With the thought process, frameworks and development around emerging technologies, sands are shifting faster than ever before.
For an outside viewer, changes are huge. What follows is not absolute technology-counterpart-comparison but rather area under the drift. Traditional RDBMS to NoSQL, traditional Web Servers to Node and nginx, from typesafe languages to dynamic typing, tradional MVC (spring/asp.net) to full stack scaffoldings (RoR), HTTP/SOAP to REST/JSON, postbacks to async, scaling up to Hadoop, ACID to CAP, proprietary data centers to cloud and the list goes on. Again, this list is not necessarily an absolute comparison of technology counterparts but these analogies have definitely come a long way since Tim O'Reilly did his famous what is web 2.0 definition and table (see below) in 2005.
| Web 1.0 | Web 2.0 | |
|---|---|---|
| DoubleClick | --> | Google AdSense |
| Ofoto | --> | Flickr |
| Akamai | --> | BitTorrent |
| mp3.com | --> | Napster |
| Britannica Online | --> | Wikipedia |
| personal websites | --> | blogging |
| evite | --> | upcoming.org and EVDB |
| domain name speculation | --> | search engine optimization |
| page views | --> | cost per click |
| screen scraping | --> | web services |
| publishing | --> | participation |
| content management systems | --> | wikis |
| directories (taxonomy) | --> | tagging ("folksonomy") |
| stickiness | --> | syndication |
For computer scientists and software engineers with sound foundation in algorithms, operating systems, database systems (including distributed databases), computer networking and enterprise architecture, the situation isn't quite hostile. There is no need to feel threatened by falling behind the learning curve due to lack of fundamental understanding and aptitude. However one should definitely be concerned if it's due to, in Seth Godin's terms, lizard brain laziness in learning and prototyping about these up and coming changes.
The fundamentals of distributed databases hasn't changed much; however the ever-networked nature of world wide web has made it more plausible then ever to use them in practice. To draw an analogy from OSI model, majority of delta is happening in the application layer. This learning curve can only be overcome through training activities learning and persistent efforts. The same way we have avoided architectural astronauts and anti-patterns by writing code and optimizing it to solve real business and technology problems, it would be bridged by coding up mapreduce or improve technical vocabulary while idling through yet another View Model implementation. At least that's how I envision it.
"Once a new technology rolls over you, if you're not part of the steamroller, you're part of the road."-Stewart Brand
