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Packaging design is one of the most important marketing tools for many manufactured packaged goods. Packaging communicates brand and product values at point of sale, and continues to work long after promotional and advertising campaigns have run their course. The design of a pack and the surface graphics are the main features that differentiate a product from its competitors. For brands or products on limited budgets, a modest investment in redesigning the pack can reap substantial dividends in terms of increased sales, improved margins and greater product profitability But there are other reasons why there is a growing interest in packaging design: – manufacturers’ brands today have to fight harder, with less shelf space, against retailers’ own brands – the internationalisation of markets means packaging design must take into account national and cultural boundaries – new materials and technology are a continuous stimulus to innovative packaging in order to boost sales, reduce costs, and increase profits – public concern with the environment and increasing legislation is putting pressure on manufacturers to redesign packaging to minimise waste and use materials, which are biodegradable or easily recyclable.
In this paper, we examine a number of SQL and socalled “NoSQL” data stores designed to scale simple OLTP-style application loads over many servers. Originally motivated by Web 2.0 applications, these systems are designed to scale to thousands or millions of users doing updates as well as reads, in contrast to traditional DBMSs and data warehouses. We contrast the new systems on their data model, consistency mechanisms, storage mechanisms, durability guarantees, availability, query support, and other dimensions. These systems typically sacrifice some of these dimensions, e.g. database-wide transaction consistency, in order to achieve others, e.g. higher availability and scalability. Note: Bibliographic references for systems are not listed, but URLs for more information can be found in the System References table at the end of this paper. Caveat: Statements in this paper are based on sources and documentation that may not be reliable, and the systems described are “moving targets,” so some statements may be incorrect. Verify through other sources before depending on information here. Nevertheless, we hope this comprehensive survey is useful! Check for future corrections on the author’s web site cattell.net/datastores. Disclosure: The author is on the technical advisory board of Schooner Technologies and has a consulting business advising on scalable databases.
In this paper, I describe some of the recent developments in the database management area, in particular the NoSQL phenomenon and the hoopla associated with it. The goal of the paper is not to do an exhaustive survey of NoSQL systems. The aim is to do a broad brush analysis of what these developments mean - the good and the bad aspects! Based on my more than three decades of database systems work in the research and product arenas, I will outline what are many of the pitfalls to avoid since there is currently a mad rush to develop and adopt a plethora of NoSQL systems in a segment of the IT population, including the research community. In rushing to develop these systems to overcome some of the shortcomings of the relational systems, many good principles of the latter, which go beyond the relational model and the SQL language, have been left by the wayside. Now many of the features that were initially discarded as unnecessary in the NoSQL systems are being brought in, but unfortunately in ad hoc ways. Hopefully, the lessons learnt over three decades with relational and other systems would not go to waste and we wouldn’t let history repeat itself with respect to simple minded approaches leading to enormous pain later on for developers as well as users of the NoSQL systems! Caveat: What I express in this paper are my personal opinions and they do not necessarily reflect the opinions of my employer.
Organizations that collect large amounts of unstructured data are increasingly turning to nonrelational databases, now frequently called NoSQL databases. M any organizations collect vast amounts of customer, scientific, sales, and other data for future analysis. Traditionally, most of these organizations have stored structured data in relational databases for subsequent access and analysis. However, a growing number of developers and users have begun turning to various types of nonrelational—now frequently called NoSQL—databases. Nonrelationa l dat a ba ses— including hierarchical, graph, and object-oriented databases—have been around since the late 1960s. However, new types of NoSQL databases are being developed. And only now are they beginning to gain market traction. Different NoSQL databases take different approaches. What they have in common is that they’re not relational. Their primary advantage is that, unlike relational databases, they handle unstructured data such as word-processing files, e-mail, multimedia, and social media efficiently. They are also easier to work with for the many developers not familiar 12 r2tec.indd 12 computer with the structured query language. SQL is the programming language used for querying and updating relational databases. Some NoSQL databases can function in a distributed setting. Users could thus scale a single database by running it across additional inexpensive machines rather than by having to run it on a single more powerful and costly machine.
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http://www.prudentialuniforms.com/services/uniforms-and-apparel/food-processing-haccp | HACCP is a management system to ensure food safety from harvest to consumption. Companies must take necessary steps to analyze and address risks from food storage, to employee uniforms, to handling procedures, in order to keep food free of contamination.
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