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Optimistic concurrency control was first proposed in 1979 by H. T. Kung and John T. Robinson. [2] OCC is generally used in environments with low data contention. When conflicts are rare, transactions can complete without the expense of managing locks and without having transactions wait for other transactions' locks to clear, leading to higher ...
Transactional memory provides optimistic concurrency control by allowing threads to run in parallel with minimal interference. [2] The goal of transactional memory systems is to transparently support regions of code marked as transactions by enforcing atomicity , consistency and isolation .
Some concurrency control strategies avoid some or all of these problems. For example, a funnel or serializing tokens can avoid the biggest problem: deadlocks. Alternatives to locking include non-blocking synchronization methods, like lock-free programming techniques and transactional memory. However, such alternative methods often require that ...
They also provide global serializability without local concurrency control information distribution, can be combined with any relevant concurrency control, and allow optimistic (non-blocking) implementations. Both use additional information for relaxing CO constraints and achieving better concurrency and performance.
In Computer Science, in the field of databases, non-lock concurrency control is a concurrency control method used in relational databases without using locking. There are several non-lock concurrency control methods, which involve the use of timestamps on transaction to determine transaction priority: Optimistic concurrency control
In computer science, software transactional memory (STM) is a concurrency control mechanism analogous to database transactions for controlling access to shared memory in concurrent computing. It is an alternative to lock-based synchronization. STM is a strategy implemented in software, rather than as a hardware component.
Multiversion concurrency control (MVCC) - Increasing concurrency and performance by generating a new version of a database object each time the object is written, and allowing transactions' read operations of several last relevant versions (of each object) depending on scheduling method.
State-based CRDTs (also called convergent replicated data types, or CvRDTs) are defined by two types, a type for local states and a type for actions on the state, together with three functions: A function to produce an initial state, a merge function of states, and a function to apply an action to update a state.