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Not ACID

Not ACID
According to Gray and Reuter, IMS supported ACID transactions in 1973 already (although the term ACID came later).[3] Characteristics[edit] The characteristics of these four properties as defined by Reuter and Härder are as follows: Atomicity[edit] Consistency[edit] Isolation[edit] Durability[edit] Examples[edit] The following examples further illustrate the ACID properties. CREATE TABLE acidtest (A INTEGER, B INTEGER, CHECK (A + B = 100)); Atomicity failure[edit] In database systems, atomicity (or atomicness; from Greek a-tomos, undividable) is one of the ACID transaction properties. Consistency failure[edit] Consistency is a very general term, which demands that the data must meet all validation rules. Isolation failure[edit] To demonstrate isolation, we assume two transactions execute at the same time, each attempting to modify the same data. Consider two transactions. T1 subtracts 10 from A.T1 adds 10 to B.T2 subtracts 10 from B.T2 adds 10 to A. Durability failure[edit] Implementation[edit]

https://en.wikipedia.org/wiki/ACID

Related:  NoSQLLooseLeaf

Distributed transaction - difficult for both SQL and NoSQL A distributed transaction is a database transaction in which two or more network hosts are involved. Usually, hosts provide transactional resources, while the transaction manager is responsible for creating and managing a global transaction that encompasses all operations against such resources. Distributed transactions, as any other transactions, must have all four ACID (atomicity, consistency, isolation, durability) properties, where atomicity guarantees all-or-nothing outcomes for the unit of work (operations bundle).

Representational state transfer Representational State Transfer (REST) is a software architecture style consisting of guidelines and best practices for creating scalable web services.[1][2] REST is a coordinated set of constraints applied to the design of components in a distributed hypermedia system that can lead to a more performant and maintainable architecture.[3] REST has gained widespread acceptance across the Web[citation needed] as a simpler alternative to SOAP and WSDL-based Web services. RESTful systems typically, but not always, communicate over the Hypertext Transfer Protocol with the same HTTP verbs (GET, POST, PUT, DELETE, etc.) used by web browsers to retrieve web pages and send data to remote servers.[3] The REST architectural style was developed by W3C Technical Architecture Group (TAG) in parallel with HTTP 1.1, based on the existing design of HTTP 1.0.[4] The World Wide Web represents the largest implementation of a system conforming to the REST architectural style. Architectural properties[edit]

1.12 Visual Tour The long awaited 1.12 version of pgAdmin III is finally available. We will try to highlight some of the new features which have been added since the last stable release. Connection handling The connection handling has been changed. Real-time web The real-time web is a network web using technologies and practices that enable users to receive information as soon as it is published by its authors, rather than requiring that they or their software check a source periodically for updates. Difference from real-time computing[edit] The real-time web is fundamentally different from real-time computing since there is no knowing when, or if, a response will be received. The information types transmitted this way are often short messages, status updates, news alerts, or links to longer documents.

Micro Service Architecture Conceptually speaking MSA is not particularly difficult to grasp but in practice it does raise many questions. How do these services communicate? What about latency between services? How do you test the services? How do you detect and respond to failure? How do you manage deployments when you have a bunch of interdependencies?

FAQ Additional FAQ Entries on this Wiki Translations of this Document Platform-specific questions Windows users should also read the platform FAQ for Windows. Why use a database instead of just saving your data to disk? This Q&A is part of a weekly series of posts highlighting common questions encountered by technophiles and answered by users at Stack Exchange, a free, community-powered network of 100+ Q&A sites. Dokkat appears to think that databases are overused. "Instead of a database, I just serialize my data to JSON, saving and loading it to disk when necessary," he writes. "All the data management is made on the program itself, which is faster AND easier than using SQL queries." What is missing here? Why should a developer use a database when saving data to a disk might work just as well?

Scalability Scalability is the capability of a system, network, or process to handle a growing amount of work, or its potential to be enlarged in order to accommodate that growth.[1] For example, it can refer to the capability of a system to increase its total output under an increased load when resources (typically hardware) are added. An analogous meaning is implied when the word is used in an economic context, where scalability of a company implies that the underlying business model offers the potential for economic growth within the company. Scalability, as a property of systems, is generally difficult to define[2] and in any particular case it is necessary to define the specific requirements for scalability on those dimensions that are deemed important.

SOLID (object-oriented design) In computer programming, SOLID (Single responsibility, Open-closed, Liskov substitution, Interface segregation and Dependency inversion) is a mnemonic acronym introduced by Michael Feathers for the "first five principles" named by Robert C. Martin[1][2] in the early 2000s[3] that stands for five basic principles of object-oriented programming and design. The principles, when applied together, intend to make it more likely that a programmer will create a system that is easy to maintain and extend over time.[3] The principles of SOLID are guidelines that can be applied while working on software to remove code smells by causing the programmer to refactor the software's source code until it is both legible and extensible. It is part of an overall strategy of agile and adaptive programming.[3]

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