This reminds me of the FML-style websites out there.
Your logo is a train crash right now. I hope its meant as an anti-web-2.0 joke otherwise there is no reason you needed to get Frank Gehry to design you a logo.
1,094 karma · joined February 26, 2010
http://fahdoo.com
This reminds me of the FML-style websites out there.
Your logo is a train crash right now. I hope its meant as an anti-web-2.0 joke otherwise there is no reason you needed to get Frank Gehry to design you a logo.
So far I'm liking it. Besides just being really well made, its great to have a place where I can get feedback on designs and works-in-progress, and to talk shop about design and development. I'm hoping it'll become my hq for all design related links/questions/inspiration.
I think you're sufficiently differentiated from Blippy and Swipely, and even if you aren't - so what? How many people outside of HN and the Valley know of these two startups? There's a ton of users to acquire and engage and you are by no means behind in the game.
I really liked your gallery implementation - did you build it from scratch?
http://quora.com (invite-only right now)
We're starting off targeting the academic market (students, researchers) but have found it pretty useful for organizing interest-based links and having general discussions as well.
Check it out http://thinkpanda.com and any feedback is appreciated!
Check it out here: http://thinkpanda.com
The basic idea is that data is stored as key > value. You can sort of relate it to the MySQL practice of denormalization and storing a bunch of data from different tables as an array in one cell.
You don't want to (or can't) do joins because data is not normalized, but instead have to process the results you would want separately in a batch process called map/reduce.
It all boils down to this one fact: NoSQL is write heavy in order to improve read performance. Because your data is in multiple places and you are doing batch processing to get the right format/calculated data then you are saving time when the user requests it from you. This is one of the reasons its good for scalability. The other reason seems to be that denormalized data is easier to scale out then normalized.
You should also look up CAP theorem and NoSQL.
A few links that I've been saving to teach myself: - http://stackoverflow.com/questions/1189911/non-relational-da... - http://stackoverflow.com/questions/2170152/nosql-best-practi... - http://www.linux-mag.com/cache/7579/1.html - http://blogs.computerworld.com/15510/the_end_of_sql_and_rela...