Atomicity (database systems) in the context of Commit (data management)


Atomicity (database systems) in the context of Commit (data management)

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⭐ Core Definition: Atomicity (database systems)

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.

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👉 Atomicity (database systems) in the context of Commit (data management)

In computer science and data management, a commit is a behavior that marks the end of a transaction and provides Atomicity, Consistency, Isolation, and Durability (ACID) in transactions. The submission records are stored in the submission log for recovery and consistency in case of failure. In terms of transactions, the opposite of committing is giving up tentative changes to the transaction, which is rolled back.

Due to the rise of distributed computing and the need to ensure data consistency across multiple systems, commit protocols have been evolving since their emergence in the 1970s. The main developments include the Two-Phase Commit (2PC) first proposed by Jim Gray, which is the fundamental core of distributed transaction management. Subsequently, the Three-phase Commit (3PC), Hypothesis Commit (PC), Hypothesis Abort (PA), and Optimistic Commit protocols gradually emerged, solving the problems of blocking and fault recovery.

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Atomicity (database systems) in the context of Transaction log

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.

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Atomicity (database systems) in the context of ACID

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.

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Atomicity (database systems) in the context of Composability

Composability is a system design principle that deals with the inter-relationships of components. A highly composable system provides components that can be selected and assembled in various combinations to satisfy specific user requirements. In information systems, the essential features that make a component composable are that it be:

  • self-contained (modular): it can be deployed independently – note that it may cooperate with other components, but dependent components are replaceable
  • stateless: it treats each request as an independent transaction, unrelated to any previous request. Stateless is just one technique; managed state and transactional systems can also be composable, but with greater difficulty.

It is widely believed that composable systems are more trustworthy than non-composable systems because it is easier to evaluate their individual parts.

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