ACID Transactions: Ensuring Data Integrity

Consistency ensures that a transaction brings the database from one valid state to another valid state. In other words, the database adheres to defined rules and constraints before and after a transaction. These rules could include data type validation, referential integrity, or business-specific logic.

Imagine a database table storing customer data with a constraint that the "age" field must be greater than or equal to 18. A transaction updating a customer's age to 15 would violate this constraint and be deemed inconsistent. Consistency ensures this violation doesn't happen, preserving data validity.

Isolation guarantees that multiple concurrent transactions happen independently of each other. A transaction shouldn't be affected by other transactions in progress, ensuring data consistency and preventing conflicts. This is achieved through mechanisms like locking, where transactions acquire locks on data resources, preventing other transactions from modifying the same data until the lock is released.

Consider two users trying to purchase the same item in an online store. Without isolation, one user might see the item available, but before completing the purchase, the other user could buy it first. This leads to inconsistent results. Isolation prevents this by ensuring each user's transaction is isolated, ensuring each user either gets the item or sees it as unavailable.

Durability ensures that once a transaction is successfully completed, the changes are permanently stored in the database. Even if the system crashes or encounters errors, the changes are not lost. This is achieved through mechanisms like logging, where the transaction's changes are written to a persistent log file before being applied to the database. If a failure occurs, the changes can be replayed from the log file, ensuring durability.

Techniques and Tools for ACID Transactions

Various techniques and tools are employed to ensure ACID properties in databases. Some of the most common include:

Locking is a widely used technique to achieve isolation. There are two main types of locks:

• Shared locks: Allow multiple transactions to read the same data simultaneously.
• Exclusive locks: Only allow one transaction to access data for writing, preventing concurrent modifications.

Locking mechanisms help prevent data inconsistency by ensuring that transactions operating on the same data don't interfere with each other.

Logging is crucial for achieving durability. When a transaction begins, its changes are written to a log file, called a transaction log. If a transaction commits successfully, the changes are applied to the database and marked as durable in the log. If a crash occurs, the log file can be used to replay uncommitted changes, ensuring the database reflects the committed transactions.

2PC is a protocol used for coordinating transactions across multiple databases or systems. It ensures that all participating systems agree to commit or rollback a transaction, ensuring atomicity across distributed environments.

2PC involves two phases:

• Prepare phase: Each participating system prepares for the transaction by writing changes to its own log but doesn't commit them yet. This ensures all systems are ready to commit together.
• Commit phase: If all systems successfully reach the prepare phase, they commit their changes. If any system fails during the prepare phase, all systems roll back their changes.

Concurrency control techniques manage access to data by multiple concurrent transactions, preventing conflicts and ensuring data consistency. Common concurrency control techniques include:

• Optimistic locking: Assumes conflicts are rare and only checks for conflicts when a transaction commits. If conflicts arise, the transaction is rolled back.
• Pessimistic locking: Assumes conflicts are frequent and acquires locks on data before accessing it, preventing other transactions from interfering.
• Multi-version concurrency control (MVCC): Provides different versions of data for different transactions, allowing multiple transactions to access and modify data concurrently without interfering with each other.

Example: Implementing ACID Transactions in SQL

Let's illustrate the ACID properties using a simple SQL example. Consider a database table named "accounts" with fields "account_id", "balance", and "customer_id".

CREATE TABLE accounts (
account_id INT PRIMARY KEY,
balance DECIMAL(10,2),
customer_id INT
);

Now, let's simulate a bank transfer transaction using SQL's transaction control statements:

BEGIN TRANSACTION;