Feel free to edit your post so as not to send people to the poor house.
220 karma · joined February 28, 2010
Previously: * Worked on big art for Burning Man with Ardent Heavy Industries and others: http://www.ardentheavyindustries.com/ * wrote a bunch of code you use when you buy tickets on Eventbrite: https://www.eventbrite.com
Feel free to edit your post so as not to send people to the poor house.
Email cubes@eventbrite.com if you're curious.
* http://www.quora.com/What-caused-Foursquares-downtime-on-Oct...
* http://blog.foursquare.com/2010/10/05/so-that-was-a-bummer/
* https://groups.google.com/group/mongodb-user/browse_thread/t...
Someone on this thread suggested that Foursquare's performance problem is related to the calculation of badges. I'm not sure where this idea came from. I haven't seen any mention of the issue being related to badges in first or secondhand sources.
That said, Mongo DB's map/reduce operation would not be a reasonable solution at this time. Mongo DB's map/reduce performance is, at present, somewhat lacking because it runs via the javascript engine which is currently single threaded. I know there are plans to improve performance of Mongo DB's javascript engine by switching to V8, but I don't know if V8 is multithreaded.
Often design decisions that look bad in hindsight get baked in early. By the time you realize that an alternate design would yield better performance, there may be too much data to migrate so you just have to live with it.
That said, there is the danger that allowing founders to hedge there risk in this fashion would make them less motivated to make their own company succeed.
For instance, the Syzygryd Kickstarter is to fund our flame effects. Our money is earmarked for prototyping and fabricating our flame effects, and any money left over goes to buying more propane for more flamey goodness.
Other solutions, such as Cassandra, MongoDB, and CouchDB provide richer semantics that make it possible to perform efficient range queries and map-reduce queries. Cassandra and MongoDB both use indices to improve query performance.
One of the primary advantages of the various NoSQL solutions is that they make it easy to scale horizontally, i.e. to add capacity by simply adding another host machine. This is in contrast to traditional relational databases, which are typically hard to scale horizontally.
As for using both, I tend to use emacs for the heavy lifting, and vi for quick edits.
Will there eventually be a large scale case of someone untrustworthy duping people via crowdsourcing? Probably. Does that mean the model is fundamentally flawed? No. Plus, crowdsourcing spreads the risk around so the loss is minimized. It's not like Bernie Madoff who insisted that investors invest all their funds through him.
* Diaspora will fail because it sounds similar to something someone else tried one time that failed.
* Nobody will use Diaspora because it will fail.
* Diaspora will fail because nobody will use it.
* Nobody will use Diaspora because it will never ship.
* Nobody will want to pay for Diaspora because nobody will want to pay for it.
* Diaspora will fail because the creators are young.
I don't know whether or not Diaspora will succeed. The old school cypherpunk in me wants to see Diaspora, or something similar, succeed. I would be more curious to see a well reasoned article on the obstacles Diaspora has to face with getting traction, and finding a viable business model.