Scale Up vs. Scale Out in Cloud Storage and Graph Processing Systems

2015 ◽  
Author(s):  
Wenting Wang ◽  
Le Xu ◽  
Indranil Gupta
Keyword(s):  
Cloud Storage ◽  
Scale Up ◽  
Graph Processing

Response to “Scale Up or Scale Out for Graph Processing”

2018 ◽  
Vol 22 (5) ◽  
pp. 18-24
Author(s):  
Semih Salihoglu ◽  
M. Tamer Ozsu
Keyword(s):  
Scale Up ◽  
Graph Processing

Big Data Computing Strategies

Big Data ◽  
2016 ◽  
pp. 793-813 ◽  
Author(s):  
Malavika Jayanand ◽  
M. Anil Kumar ◽  
K. G. Srinivasa ◽  
G. M. Siddesh
Keyword(s):  
Big Data ◽  
Case Studies ◽  
Cloud Storage ◽  
Scale Up ◽  
Application Integration ◽  
Cloud Environment ◽  
Key Concepts ◽  
Business Opportunities ◽  
Big Data Computing

In order to store these huge bulks of data, organizations have to buy servers and scale it according to their need. One of the solution for storage would be Cloud Environment as there is no need to scale up storage by aggregating more physical servers, installing, updating, or to run backups, which also cuts down system hardware and makes application integration easier. This chapter discusses key concepts of cloud storage as storage as a solution for Big data, different big data domains, and its application with case studies of how organizations are leveraging Big data for better business opportunities.

Big Data Computing Strategies

2015 ◽  
pp. 72-90
Author(s):  
Malavika Jayanand ◽  
M. Anil Kumar ◽  
K. G. Srinivasa ◽  
G. M. Siddesh
Keyword(s):  
Big Data ◽  
Case Studies ◽  
Cloud Storage ◽  
Scale Up ◽  
Application Integration ◽  
Cloud Environment ◽  
Key Concepts ◽  
Business Opportunities ◽  
Big Data Computing

In order to store these huge bulks of data, organizations have to buy servers and scale it according to their need. One of the solution for storage would be Cloud Environment as there is no need to scale up storage by aggregating more physical servers, installing, updating, or to run backups, which also cuts down system hardware and makes application integration easier. This chapter discusses key concepts of cloud storage as storage as a solution for Bigdata, different big data domains, and its application with case studies of how organizations are leveraging Bigdata for better business opportunities.

Scale Up or Scale Out for Graph Processing?

2018 ◽  
Vol 22 (3) ◽  
pp. 72-78 ◽  
Author(s):  
Jimmy Lin
Keyword(s):  
Scale Up ◽  
Graph Processing

NiAl precipitation in Fe-12w/o Cr-5w/o Ni-4w/o Al

1983 ◽  
Vol 41 ◽  
pp. 202-203
Author(s):  
L.E. Murr ◽  
J.S. Dunning ◽  
S. Shankar
Keyword(s):  
Solid Solution ◽  
Stainless Steel ◽  
Stainless Steels ◽  
Alloy Composition ◽  
Chromium Content ◽  
Scale Up ◽  
Optical Metallography ◽  
Property Evaluation ◽  
310 Stainless Steel ◽  
Microstructural Studies

Aluminum additions to conventional 18Cr-8Ni austenitic stainless steel compositions impart excellent resistance to high sulfur environments. However, problems are typically encountered with aluminum additions above about 1% due to embrittlement caused by aluminum in solid solution and the precipitation of NiAl. Consequently, little use has been made of aluminum alloy additions to stainless steels for use in sulfur or H2S environments in the chemical industry, energy conversion or generation, and mineral processing, for example.A research program at the Albany Research Center has concentrated on the development of a wrought alloy composition with as low a chromium content as possible, with the idea of developing a low-chromium substitute for 310 stainless steel (25Cr-20Ni) which is often used in high-sulfur environments. On the basis of workability and microstructural studies involving optical metallography on 100g button ingots soaked at 700°C and air-cooled, a low-alloy composition Fe-12Cr-5Ni-4Al (in wt %) was selected for scale up and property evaluation.

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