In our previous articles « why language choice doesn’t matter for your development project » and « why language choice does matter for your development project », we have taken absurdly strong positions in favor and against the selection of a specific development language for a given project.
This post points out the reasons that make choosing a language for a specific project relevant. Of course, you can find online articles that explain “Why language choice does not matter for your development project”. In the end, the choice is yours!
This post points out the reasons that make choosing a language for a specific project irrelevant. Of course, you can find online articles that explain “Why language choice does matter for your development project”. In the end, the choice is yours!
You got it, in this blog we are talking about CEP and Event Stream Processing (ESP). In recent years, we have seen a lot of interest in “context-aware” applications or, if you prefer, detecting in real-time interesting contexts. But, if you look at tech blogs or even at IT vendors you can sometimes see ESP, CEP or pattern matching engines for this kind of applications. So what? If I need to be able to react in Real-time to interesting situations (business wise) by processing Streams of Events which one should I use? Are they the same? If I do complex things when I process my event stream do I really do Complex Event Processing? Then, does it mean that I need a CEP ?” These are really interesting questions that I will try to answer in this post.
The GPU Technology Conference is one of those events where cutting-edge technology meets industrial players who are either see an opportunity to invest in the future trends or are able to match actual problems with the new abilities enabled by the technology. It is the place where the recent developments in the domain of GPU computing get presented, along with a showcase of all the challenges that the GPU technology has resolved so far. For a company such as EURA NOVA, this is the place where existing solutions meets new challenges that require innovation.
Data reuse in health care is a vast topic, one problematic being the anonymization of the data themselves. This is such a complex problem that it’s usually the one in the spotlights, but it is useful sometimes to remind ourselves why working out the data is needed. Let us imagine briefly that we have solved the matter and reflect only on the opportunities and solutions Big Data technologies bring.
With the holiday season approaching, brands are releasing the product that they want us to buy to our relatives (or to ourselves).
These past years the Graphics Processing Units have gained popularity and momentum in industrial research thanks to the parallel processing power (# of parallel core) that these offers for a reasonable price. The second reason behind this is their wide hardware availability in the consumer landscape: the sheer price cost of a GPU has favored their presence in most of the consumer devices nowadays, from mobile phones & tablets to video game systems.
IS THE FUTURE OF BUSINESS TOTALLY HUMAN CENTRIC?
Today, we see a lot of young developers and designers that grew up with technologies, new social habits and a lot of new tools that did not exist for the previous generation (actually, a generation is no more than 10 years today!).
As a consequence, entrepreneurs in their early 20’s are creating and innovating using technical stacks they have known their whole life, unaware of the details of a CPU, who Turing was and what a methodology can bring to a development project. They just create and diffuse their ideas!
… and people consume their products, get new habits and change their way of viewing/judging things.
In this blog post we briefly describe our new contribution to the big data domain, especially, graphDB benchmarking. This work was accepted for publication at 2013 ASE/IEEE International Conference on Big Data.
In this work, we presented a distributed graph database benchmarking framework. We used this tool to analyze the performance of four graph databases: Neo4j 1.9M05 , Titan 0.3, OrientDB 1.3 and DEX 4.7.