Understanding Concurrency Control in Databases

Organized collection of data in computing.

Concurrency control in databases is a critical aspect of database management systems (DBMS). It ensures the correct execution of transactions in a multi-user database environment, maintaining the consistency, isolation, and durability (ACID) properties of the database.

What is Concurrency Control?

Concurrency control is a method used in DBMS to manage simultaneous operations without conflicting with each other. In a multi-user database environment, concurrency control ensures that correct results for concurrent operations are generated, while preserving data integrity.

Importance of Concurrency Control in Databases

Concurrency control is crucial for several reasons:

1. Data Consistency: Concurrency control ensures that a database remains consistent even after multiple simultaneous transactions.

2. Isolation: It ensures that each transaction is executed in isolation, i.e., the execution of one does not affect the execution of another.

3. Performance: By allowing multiple transactions to execute concurrently, it improves the overall speed and throughput of the system.

Problems Without Concurrency Control

Without proper concurrency control, several issues can arise:

1. Dirty Read: A transaction reads data written by a non-committed transaction.

2. Non-Repeatable Read: A transaction reads the same row twice and gets different data each time.

3. Phantom Read: A transaction re-executes a query returning a set of rows that satisfy a search condition and finds that the set of rows satisfying the condition has changed due to another recently-committed transaction.

4. Lost Update: Two transactions both read a row, one writes to it and commits, and then the second writes to it and commits, overwriting the first transaction's write.

Overview of Concurrency Control Techniques

There are several techniques for managing concurrency control in databases:

1. Lock-Based Concurrency Control: This is the most common form of concurrency control. It involves locking data items whenever a transaction accesses them.

2. Timestamp-Based Concurrency Control: This method uses timestamps to decide the order of transaction execution to prevent conflicts.

3. Optimistic Concurrency Control: This method assumes that conflicts of transactions are rare and allows transactions to execute without checking for conflicts initially.

4. Multiversion Concurrency Control (MVCC): This method allows multiple versions of a data item to exist simultaneously in the database. It improves performance by allowing more transactions to execute concurrently.

In the next unit, we will delve deeper into these techniques and learn how to implement them in Rust.