Top 10 cloud trends for 2016

cloud-adoption-trends

Good post by Lazlo Creates (thank you)

Just like any other area of technological innovation, cloud is a massive industry which has developed in ways few would predict a couple of years ago. As more individuals and enterprises embrace cloud technologies, the security and usability questions become a central focus of many providers. But consumer expectations aren’t the only factor shaping the state of cloud. Here are 10 key cloud trends to watch in 2016.

Read on here

The Storage Requirements for 100% Virtualization

Post by George Crump (thank you)

After a rapid move from test to production, virtualization of existing servers in many companies seems to slow down. While it is true that most data centers have adopted a virtualize first philosophy, getting those older, mission critical workloads virtualized seems to be a thorny issue. These applications are often at the heart of an organization’s revenue or customer interaction and tend to be unpredictable in the resources they require. This is especially true when it comes to storage and networking.

Read on here

Flash, Trash and data-driven infrastructures!

Post by Enrico Signoretti (thank you)

I’ve been talking about two-tier storage infrastructures for a while now. End users are targeting this kind of approach to cope with capacity growth and performance needs. The basic idea is to leverage Flash memory characteristics (All-flash, Hybrid, hyperconvergence) on one side and implement huge storage repositories, where they can safely store all the rest (including pure Trash) at the lowest possible cost, on the other. The latter is lately also referred to as a data lake.

Read on here

Thinking different about storage

Good post by Enrico Signoretti (thank you)

In the last few months I had several interesting briefings with storage vendors. Now, I need to stop and try to connect the dots, and think about what could come next.
It’s incredible to see how rapidly the storage landscape is evolving and becoming much smarter than in the past. This will change the way we store, use and manage data and, of course, the design of future infrastructures.

Read on here

Qumulo emerges with data-aware scale-out NAS

Good post by Dave Raffo (thank you)

Isilon founding engineers launch Qumulo Core, software designed to manage scale-out NAS with real-time analytics.

Qumulo came out of stealth today with what it describes as data-aware scale-out NAS with real-time analytics built in.

Qumulo Core was developed by many of the same developers who created Isilon scale-out NAS. Qumulo founders Peter Godman, Aaron Passey and Neal Fachan were responsible for dozens of Isilon patents. EMC acquired Isilon for $2.25 billion in 2010.

Read on here

Hadoop: A Storage Platform as Well as Analysis Tool?

Post by Michele Nemschoff (thank you)

Data warehouses are a critical component for enterprises seeking to gain insights from the data they collect, but as the volume of data businesses collect continues to grow, the traditional data warehouse is increasingly becoming too expensive to maintain. On top of this, the majority of data being created today is unstructured data, which a traditional database is unable to collect and store unless the data is converted into a structured form.

Read on here

IBM Research Accelerating Discovery: Social Analytics

IBM PureData System for Operational Analytics vs Oracle Exadata X3

whitepaper_download

Good Whitepaper by Bloor Research (Philip Howard) – thanks !

The basic theme of this paper is to provide a comprehensive comparison of IBM’s and Oracle’s offerings for large-scale traditional data warehousing environments. These envi- ronments run to thousands of concurrent queries, a large proportion of which (up to 80% typically) are simple look-up queries. These are combined with more complex analytics, which means that maintaining a balance between these different query types is espe- cially important in these environments. In addition, there is significant demand for near real-time views of operational data held within the data warehouse and for real-time analytics, which requires the ability to load data into the warehouse on a continuous basis. In the case of IBM this means IBM PureData System for Operational Analytics and, in the case of Oracle, Exadata 3-2.

Get the Whitepaper here