Database
“You just can't have it all” is a phrase that most of us are accustomed to hearing and that many still believe to be true when discussing the speed, scale and cost of processing data. To reach high speed data processing, it is necessary to utilize more memory
cloud
A series of recent surveys on the subject seems to indicate that this is indeed the case: Research conducted by HP found that the majority of businesses in the EMEA region are planning to move their mission-critical apps to the cloud. Of the 940 respondents, 80 percent revealed plans to
analytics
Making Hadoop Run Faster One of the challenges in processing data is that the speed at which we can input data is quite often much faster than the speed at which we can process it. This problem becomes even more pronounced in the context of Big Data, where the volume
amazon
Cloud bursting is an application deployment model in which an application runs in a private cloud or data center and bursts into a public cloud when the demand for computing capacity spikes. The advantage of such a hybrid cloud deployment is that an organization only pays for extra compute resources
nosql
Major social networking platforms like Facebook and Twitter have developed their own architectures for handling the need for real-time analytics on huge amounts of data. However, not every company has the need or resources to build their own Twitter-like solution. In this example we have taken the same Twitter/Facebook-like
nosql
Edd Dumbill wrote an interesting article on O’Reilly Radar covering the current solutions for running Big Data in the Cloud Big data and cloud technology go hand-in-hand. Big data needs clusters of servers for processing, which clouds can readily provide. Big PaaS Edd touched briefly on the role of
administrator
The term "cloud portability" is often considered a synonym for "Cloud API portability," which implies a series of misconceptions. If we break away from dogma, we can find that what we really looking for in cloud portability is Application portability between clouds which can be a
scalabilty
It's time to think of the architecture and application platforms surrounding "Big Data" databases. Big Data is often centered around new database technologies mostly from the emerging NoSQL world. The main challenge that these databases solve is how to handle massive amount of data at a
analytics large database real time
Recently, I was reading Todd Hoff's write-up on FaceBook real time analytics system . As usual, Todd did an excellent job in summarizing this video from Engineering Manager at Facebook Alex Himel. In the first post, I’d like to summarize the case study, and consider some things that
administration
Lately I've been reading more cases were different people have started to realize the limitations of the NoSQL promise to database scalability. Note the references below: * Why does Quora use MySQL as the data store instead of NoSQLs such as Cassandra, MongoDB, CouchDB etc? * Why did Diaspora abandon
gigaspaces
Yesterday, I had a session during the OpenStack Summit where I tried to present a more general view on how we should be thinking about PaaS in the context of OpenStack. The key takeaway : The main goal of PaaS is to drive productivity into the process by which we can
cloud computing
A recent study showed that over 92 percent of executives from leading retailers are focusing their marketing efforts on Facebook and subsequent applications. Furthermore, over 71 percent of users have confirmed they are more likely to make a purchase after “liking” a brand they find online. (source ) Sears Architect Tomer
gigaspaces
Gartner published recently an interesting paper: Productivity vs. Control: Cloud Application Platforms Must Split to Win . (The paper requires registration.) The paper does a pretty good job covering the evolution that is taking place in the PaaS market toward a more open platform and compares between the two main categories:
Unlike many of the existing Platforms, in this second-generation phase, its not going to be enough to package and bundle different individual middleware services and products (Web Containers, Messaging, Data, Monitoring, Automation and Control, Provisioning) and brand them under the same name to make them look as one. (Fusion? Fabric?
In many of the recent discussions on the design of large scale systems (a.k.a. Web Scale) it was argued that the right set of tradeoffs for building large scale systems would be to give away Consistency for Availability and Partition tolerance. Those arguments relied on the foundation of
In the past year, Intel issued a series of powerful chips under the new Nehalem microarchitecture , with large numbers of cores and extensive memory capacity. This new class of chips is is part of a bigger Intel initiative referred to as Tera-Scale Computing . Cisco has released their Unified Computing System