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5 Important Factors for Pricing Data in the Information (Overload) Age
This guest post comes from Nick Ducoff, Co-founder and CEO of Infochimps , an Austin-based marketplace to find, share and build on data. He blogs at nick.vc . Do you remember what it was like to figure out what was going on in your city fifteen years ago? You probably called your friends.
Dirty data, stored dirt cheap | DBMS 2 : DataBase Management System Services
June 4, 2011 A major driver of Hadoop adoption is the “big bit bucket” use case. Users take a whole lot of data, often machine-generated data in logs of different kinds, and dump it into one place, managed by Hadoop, at open-source pricing. Hadoop hardware doesn’t need to be that costly either. And once you get that data into Hadoop, there are a whole lot of things you can do with it . Of course, there are various outfits who’d like to sell you not-so-cheap bit buckets.
June 4, 2011 After suggesting that there’s little point to Hadoop appliances , it occurred to me to look into what kinds of hardware actually are used with Hadoop. So far as I can tell: Most Hadoop deployments today use systems with dual socket and quad or hex cores (8 or 12 cores total, 16 or 24 hyper-threaded). Storage has increased as well with 6-8 spindles being common and some deployments going to 12 spindles. These are SATA disks with between 1TB and 2TB capacity.
Hardware for Hadoop | DBMS 2 : DataBase Management System Services
If you’re writing a serious application, on the web or otherwise, you’ve got to have good logging. In the context of application development, reading logs is my personal favorite method for tracking bugs and rooting them out. A service like Loggly is perfect for programmers like me. It provides an easy to use web interface with searching capabilities that allows you to see what your application is logging at any time that you’d like to check in. Debugging with Loggly is nice, but it’s just the tip of the iceberg, thanks in part to its Loggly API .
Stack Your Logs In One Place With Loggly
The most audacious start-up pitches are those that propose changing people's communications habits. No matter how clever a company's technology or gorgeous an app's interface, getting users to adopt new modalities of communication is perhaps the hardest job in tech. It's a social challenge as much as a technological one, which means that if you get it right, your technology spreads from person to person--virally, as the overused term calls it.
CloudTalk: Voice instant messaging that works | Rafe's Radar - CNET News
BPM Academy On-demand webinars and podcasts: The BPM Primer is recently updated and designed to bring you up-to-speed on all things BPM. In this 35-minute webinar Andrew Spanyi will provide an introductory overview to take you from BPM Beginner to BPM Brainiac, including real-world examples of BPM's value. Learn more »
What is BPM | BPMBasics Learning Center | Appian BPM
Introduction to SMPP
MMS notifications, when users pay for ringtones and Java applications, the download location is send by a MMS notification or WAP Push message; SMPP is used by clients to connected to a SMSC (Short Message Service Centre). In SMPP terms, the client is called ESME (Extended Short Message Entity). SMSC's can also exchange data using a SMPP connection.
IKS chat
My guests on this Talking with Talis podcast are Wernher Behrendt and John Pereira of Salzburg Research. They are part of the team behind IKS – The Interactive Knowledge Stack an Integrating Project part-funded by the European Commission. The four year project started in January 2009 to provide an open source technology platform for semantically enhanced content management systems.eXtremeDB is a high performance, low-latency, ACID -compliant embedded database management system using an in-memory database system (IMDS) architecture and designed to be linked into C / C++ based programs. It works on Windows , Linux , and other real-time and embedded operating systems. Building on this core IMDS, there are several editions supporting high availability , database clustering, hybrid (in-memory and disk-based) data storage and other specialized abilities. [ edit ] History eXtremeDB initially targeted real-time embedded systems running in resource-constrained environments (i.e. with limited random-access memory (RAM) and relatively low-powered central processing units (CPU)). eXtremeDB characteristics appealing to this market include a small code size (approximately 150 KB), native C language application programming interface (API), available source code, and a high degree of portability (to support the varied processors and operating systems used in embedded systems ).
