Database vendor choice is one of the factors affecting the cost of provision of data. Even when licensing pricing is unpredictable we need database pricing to be low and stable. The pricing model can be per storage/ per server or user based where users need to create their separate profiles. Another type of models is in which cost structure have an influence over architecture where customers are not able to get all the expected cloud features such as independently scaling computing and storage. Computing and storage should be priced independently. This works well in case of the seasonality of data where one only has to pay for what he uses. Read more at https://gigaom.com/2017/05/08/know-your-embedded-database-cost/

Starting a small business can seem tough and impossible at first when, there is so much to do on the front end before you even open the doors for your customers . We are now in the age of the art of technology which uses cloud computing to store all of our information and access if from anywhere we are. Not only does this make operating a business easier, but it makes the process much more efficient. The cloud can be your secret weapon to any aspect of the start-up process of your business. Here’s how.

Read more at:  http://www.business2community.com/cloud-computing/6-ways-use-cloud-start-business-01669177#o3OZvYPJyqBGeKit.99

Big Data’s prospects are tremendous and will keep growing but only if we can keep up with it. Bangalore now monitors traffic in real time. It is only then that Data Analytics steps in, helping take calculated decisions for the strategic spots for sign boards and road markings. Thereby reducing congestion and allowing safer travel. We see how crucial the hardware, software, networking and data center are in the analysis of such data. Analytical data mining seems to be the majority of the effort now. Smarter data centers, networking practices and rapid storage technologies will be the start of a cycle of innovation that may be a few decade long. Ironically enough, in-depth analytics generates data that has greater need for computation and large storage systems that will allow rapid testing and deployment. Read more at: http://www.firstpost.com/business/big-data-paradox-2323460.html

Smartphones are fantastic examples of devices whose success largely depends on the performance it delivers. Big data researchers are working towards developing the network, computing and cloud architecture required to sustain their projects. The sheer volume of data generated by us doubles every two years and there is an urgency to make storage devices manageable and affordable. SSA (Solid State Array) at the hardware level and SDS (Software-Defined Storage] at the software level are becoming quickly affordable. With the evolution of in-device memory, a variety of data will now come into light that may revolutionize the applications of Big Data in the mobile industry. In-memory databases will allow real-time analytics and awareness of the ‘live’ transaction data – rather than delayed ‘fact-based’ analysis of old data. Read more at: http://www.forbes.com/sites/howardbaldwin/2015/06/22/flash-ways-to-make-big-data-run-faster/

Kinesis is a service related to real-time processing of streaming data. It buffers data into a storage system with checkpoints to absorb the data into the Redshift cloud data warehouse. Users can store and process large datasets each hour from various sources like financial transactions, social media feeds, location-tracked events etc. With Kinesis, business customers can write applications, generate alerts, and make other decisions virtually apart from retrieving the stored data back instantly. According to Amazon, Kinesis can support applications and data streams of any size while replicating across multiple availability zones. Kinesis has been positioned as an answer to big data, with a “pay-as-you-go” pricing.

To read more, visit the following link:

http://www.zdnet.com/kinesis-amazon-web-servicess-answer-to-big-data-7000023223/