عنوان مقاله
بررسی پیرامون پایگاههای داده NoSQL
فهرست مطالب
مقدمه
مفاهیم عمومی
حافظه های کلید – مقدار
حافظه های سند
حافظه های رکورد توسعه پذیر
نتیجه گیری
بخشی از مقاله
خطا و خرابی گردانی (اداره خرابی ها):
به منظورتحمل خرابی های ناشی از میزبان های ذخیره موقتاً غایب، Dynamo از شیوه حد نصاب اکید استفاده نمی کند، بلکه از شیوه sloopy استفاده می کند. این شیوه ها نشان می دهند که در مورد عملیات های خواندن و نوشتن، N گره سالم اول لیست اولویت آیتم داده ای مورد توجه قرار می گیرد. معیار دوم برای اداره میزبان های ذخیره موقتاً غایب، hinted handoff نامیده شده اند. آنها زمانی نقش ایفا می کنند که گره در طول عملیات نوشتن آیتم داده که مسئولیت آن را برعهده دارند، قابل دسترسی نباشد.
کلمات کلیدی:
A Survey on NoSQL Databases Santhosh Kumar Gajendran 1. Abstract NoSQL databases have gained popularity in the recent years and have been successful in many production systems. The goal of this document is to understand the current needs that have led to the evolution of NoSQL data stores, why relational database systems were not able to meet these requirements and a brief discussion of some of the successful NoSQL data stores. We will study the common concepts underlying these data stores and how they compromise on ACID properties to achieve high scalability and availability. We also look at how the database community looks at this evolution: will it supersede the RDBMS (or) just a passing cloud? 2. Introduction Data management systems began by automating traditional tasks like recording transactions in business, science, and commerce. These systems have evolved over the time from the manual methods through the several stages of automated data management. The idea of relational model emerged with E.F.Codd’s 1970 paper [1] which made data modeling and application programming much easier than in the past. Beyond the intended benefits, the relational model was well-suited to client-server programming and have proved to be the predominant technology for storing structured data in web and business applications. Applications also evolve with time and pose challenging demands for the data management. As stated by Jim Gray [6], the most challenging part is to understand the data and find patterns, trends, anomalies and extract the relevant information. With the advent of Web 2.0 applications, the data stores needed to scale to OLTP/OLAP-style application loads where millions of users read and update, in contrast to the traditional data stores. These data stores need to provide good horizontal scalability for the simple read/write operations distributed over many servers. The relational database systems have little capability to horizontally scale to these levels. So, this paved the way to seek alternative solutions for scenarios where relational database systems proved to be not the right choice. 3. Background The term ”NoSQL” was first coined in 1998 by Carlo Strozzi [2] for his RDBMS, Strozzi NoSQL. However, Strozzi coined the term simply to distinguish his solution from other RDMBS solutions which utilize SQL (Strozzi’s NoSQL still adheres to the relational model). He used the term NoSQL just for the reason that his database did not expose a SQL interface. Recently, the term NoSQL (meaning ’not only SQL’) has come to describe a large class of databases which do not have properties of traditional relational databases and which are generally not queried with SQL (structured query language). The term revived in the recent times with big companies like Google/Amazon using their own
