Database transaction in the context of Rollback (data management)

Screening in economics refers to a strategy of combating adverse selection – one of the potential decision-making complications in cases of asymmetric information – by the agent(s) with less information.

For the purposes of screening, asymmetric information cases assume two economic agents, with agents attempting to engage in some sort of transaction. There often exists a long-term relationship between the two agents, though that qualifier is not necessary. Fundamentally, the strategy involved with screening comprises the “screener” (the agent with less information) attempting to gain further insight or knowledge into private information that the other economic agent possesses which is initially unknown to the screener before the transaction takes place. In gathering such information, the information asymmetry between the two agents is reduced, meaning that the screening agent can then make more informed decisions when partaking in the transaction. Industries that utilise screening are able to filter out useful information from false information in order to get a clearer picture of the informed party. This is important when addressing problems such as adverse selection and moral hazard. Moreover, screening allows for efficiency as it enhances the flow of information between agents as typically asymmetric information causes inefficiency.

In the field of databases in computer science, a transaction log (also transaction journal, database log, binary log or audit trail) is a history of actions executed by a database management system used to guarantee ACID properties over crashes or hardware failures. Physically, a log is a file listing changes to the database, stored in a stable storage format.

If, after a start, the database is found in an inconsistent state or not been shut down properly, the database management system reviews the database logs for uncommitted transactions and rolls back the changes made by these transactions. Additionally, all transactions that are already committed but whose changes were not yet materialized in the database are re-applied. Both are done to ensure atomicity and durability of transactions.

An equity issuance or equity issue is the sale of new equity or capital stock by a firm to investors. Equity issuance can involve a private sale, in which the transaction between investors and the firm takes place directly, or publicly, in which case the firm has to register the securities with the authorities and the sale takes place in an organized market, open to any registered investor, a process more akin to an auction. Two common types of public equity issuance are initial public offerings (IPOs) and secondary equity offerings (SEOs or FO). This is one of the ways firms finance themselves, that is, they obtain funds from investors in order to engage in business.

In computer science, ACID (atomicity, consistency, isolation, durability) is a set of properties of database transactions intended to guarantee data validity despite errors, power failures, and other mishaps. For example, a transfer of funds from one bank account to another, involving multiple changes such as debiting one account and crediting another, is a single transaction.

In 1983, Andreas Reuter and Theo Härder coined the acronym ACID, building on earlier work by Jim Gray who named atomicity, consistency, and durability, but not isolation, when characterizing the transaction concept. These four properties are the major guarantees of the transaction paradigm, which has influenced many aspects of development in database systems.

In database systems, consistency (or correctness) refers to the requirement that any given database transaction must change affected data only in allowed ways. Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof. This does not guarantee correctness of the transaction in all ways the application programmer might have wanted (that is the responsibility of application-level code) but merely that any programming errors cannot result in the violation of any defined database constraints.

In a distributed system, referencing CAP theorem, consistency can also be understood as after a successful write, update or delete of a Record, any read request immediately receives the latest value of the Record.

An example of transaction atomicity could be a digital monetary transfer from bank account A to account B. It consists of two operations, debiting the money from account A and crediting it to account B. Performing both of these operations inside of an atomic transaction ensures that the database remains in a consistent state, if either operation fails there will not be any unaccountable credits or debits affecting either account.

In database systems, durability is the ACID property that guarantees that the effects of transactions that have been committed will survive permanently, even in cases of failures, including incidents and catastrophic events. For example, if a flight booking reports that a seat has successfully been booked, then the seat will remain booked even if the system crashes.

Formally, a database system ensures the durability property if it tolerates three types of failures: transaction, system, and media failures. In particular, a transaction fails if its execution is interrupted before all its operations have been processed by the system. These kinds of interruptions can be originated at the transaction level by data-entry errors, operator cancellation, timeout, or application-specific errors, like withdrawing money from a bank account with insufficient funds. At the system level, a failure occurs if the contents of the volatile storage are lost, due, for instance, to system crashes, like out-of-memory events. At the media level, where media means a stable storage that withstands system failures, failures happen when the stable storage, or part of it, is lost. These cases are typically represented by disk failures.