# optimistic-locking Published articles for optimistic-locking. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Database Locking Mechanisms DevFeed: [Database Locking Mechanisms]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-05-19T06:27:39Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [Databases](), [Concurrency](), [Deadlock](), [Transactions](), [SQL](), [Object-relational mapping]() Tags: [concurrency](), [consistency](), [database](), [hibernate](), [locking](), [locks](), [optimistic-locking](), [sql](), [transactions]() ### AI overview This tutorial compares pessimistic and optimistic locking for maintaining data consistency in multi-user applications. Pessimistic locking acquires locks before updates, while optimistic locking detects conflicts at commit time using version numbers or timestamps. The article explains their trade-offs in concurrency, performance, deadlocks, and consistency, and outlines suitable use cases. ### Source excerpt Pessimistic vs Optimistic ## Optimistic Locking Overview DevFeed: [Optimistic Locking Overview]() Original publisher: [Read original article]() Author: somesh sharma Published: 2025-06-19T09:02:40Z Content type: tutorial Language: en Sources: [Housing.com]() Topics: [Concurrency](), [Transactions](), [Database]() Tags: [concurrency](), [concurrency-control](), [database](), [databases](), [isolation-level](), [locks](), [optimistic-locking](), [retry](), [sql](), [stateless](), [transaction-management](), [transactions]() ### AI overview An overview of optimistic locking as a concurrency-control mechanism for database transactions. It explains how version columns detect conflicting updates, when optimistic locking is suitable, and when transaction isolation may make it unnecessary. ### Source excerpt Optimistic locking is a concurrency control mechanism where we assume that multiple transactions can safely access data without conflict, allowing them to proceed without locking the data upfront. Unlike pessimistic locking, where resources are locked to avoid conflicts, optimistic locking allows transactions to proceed without locks and checks for conflicts only when updating the data. If a conflict is detected (e.g., another transaction has already modified the data), the operation fails, and you can retry it. When Should You Use Optimistic Locking? Optimistic locking is ideal for use in scenarios where: Low contention exists: If it's unlikely that multiple users or processes will try to update the same data at the same time, optimistic locking is a good fit. This is especially true in systems where most operations involve reading data rather than writing it. High read-to-write ratio: If your application is mostly about reading data and writing happens less frequently, optimistic locking helps avoid the overhead of locking rows during reads. Non-critical updates: In cases where it's okay to retry a failed update without much impact, optimistic locking is a good choice. When conflicts arise, either the user or the system can simply retry. Stateless operations: Optimistic locking is suitable in stateless environments where holding onto locks across multiple requests or sessions isn't feasible. Long-running transactions: If your transactions take a long time to complete, holding locks during the entire process isn't feasible. Optimistic locking provides flexibility while still maintaining data integrity. How Optimistic Locking Works in Databases In databases, optimistic locking is usually implemented with a version column. Each row in the database has a version field (like a number or timestamp) that gets updated whenever the row is modified. When updating a record, the database checks if the version in the database matches the version the transaction originally read ## Optimistic locking pitfalls DevFeed: [Optimistic locking pitfalls]() Original publisher: [Read original article]() Published: 2017-04-27T00:00:00Z Content type: tutorial Language: en Sources: [Paweł Chudzik]() Topics: [Concurrency](), [Transactions](), [.NET 11 Preview 7]() Tags: [concurrency-control](), [consistency](), [hibernate](), [java](), [jpa](), [locking](), [optimistic-locking](), [pitfalls](), [transactions]() ### AI overview This article explains optimistic locking as a concurrency-control technique and examines how plain SQL and JPA/Hibernate version checks prevent one user from unintentionally overwriting another user's changes. ### Source excerpt Optimistic locking is concurrency control method that allows to execute multiple transactions simultaneously as long as they don't interfere which each other. That's definition from wikipedia. You probably already know that Hibernate supports optimistic locking and all you have to do in order to implement optimistic locking in you app is to add @Version on number or timestamp field and you are good to go. Right? Read more