Modern applications rely upon databases not just to store data, but to ensure that it remains accurate, consistent, and secure, even when accessed or edited by multiple users in parallel. At the core of this is the reliability of SQL transactions, which govern how the system performs data operations consistently, reliably, and safely.
A SQL transaction consists of one or more data operations (insert, update, delete, etc) that can be added into a logical unit of work that must complete or fail together. To help guarantee that a group of operations either fully completes or leaves the database unchanged if any part of that operation fails, we use transactions.
For example, think of a banking system that allows transfers of money from one account to another. In this situation, you need to debit one account and credit another. If either of these operations fails, and if the transaction didn’t roll back, you could have some very confused users and some serious financial discrepancies.
SQL transactions are governed by a set of principles know as ACID – Atomicity, Consistency, Isolation, and Durability – in addition to the concept of isolation levels, which further define how transactions relate to each other. Together, the eight components frame data integrity in a relational database system.
Transactions are especially critical in systems with high concurrency, where multiple users or applications access the database simultaneously. Without transactions, data could easily become inconsistent or corrupt during such access.
The ACID Properties
To support reliable transactions, database systems must abide by the four fundamental properties, referred to collectively as ACID.
1. Atomicity
Atomicity treats all parts of a transaction as a single unit, even if they involve separate operations. If any operation fails, the system cancels the entire transaction and restores the database to its original state. This prevents a failed transaction from resulting in partial updates and therefore leaves the data in an unpredictable state.
2. Consistency
Consistency guarantees that the transaction takes the database from one valid state to another valid state while maintaining the integrity of the rules, constraints, and conditions of the data. After the transaction, the database must be in compliance with all of its integrity constraints including unique keys, foreign keys, and checks.
3. Isolation
Isolation guarantees that operations in a transaction do not interfere with each other. This means the intermediate states of a transaction are hidden from other transactions until the first transaction is committed. This is critical in a multi-user environment to help prevent conflicts.
4. Durability
Durability ensures that once a transaction commits, the system saves the changes to non-volatile storage, where they remain—even during a power outage or system crash.
SQL Isolation Levels
Transactions are often executed concurrently in a multi-user environment, and to control the concurrency of transactions to prevent dirty reads, lost updates, and phantom reads, SQL databases use isolation levels. Isolation levels provide a means to specify how far the result of a transaction is isolated from other transactions.
Read Uncommitted
Read Uncommitted is the lowest level of isolation. Transactions are allowed to read information that is modified by another transaction but not committed. The results can be
- Dirty Reads: Reading information that could be rolled back.
- Non-repeatable: Different results for more than one read of the same row in the transaction.
- Phantom Reads: See instances of a new row added by another transaction in a separate read.
It is quick, but not guaranteed for accuracy.
Read Committed
At the Read Committed level, a transaction can only read data that has been committed by another transaction; therefore, dirty reads not possible but it is still possible to get non-repeatable and/or phantom reads.
Most, if not all, relational databases, (Oracle and SQL Server as examples) use Read Committed level as a default.
Repeatable Read
Repeatable Read guarantees that if a transaction reads a row of data once, it will see the same value if it reads the row again later in the same transaction. It successfully prevents dirty and non-repeatable reads but it does not protect against phantom reads. This isolation level finds the balance between Consistency and Performance.
Serializable
This is the most stringent isolation level. It guarantees complete isolation, because it makes any transaction look like it is running in any order. Serializability ensures that you prevent any concurrency issues with dirty reads, non-repeatable reads, or phantom reads. However, it does greatly reduce performance when locking and blocking occur.
Why ACID and Isolation Levels are important
If ACID properties and isolation levels are not considered, you will suffer issues in your database stability, reliability, and consistency as it relates to heavy load and concurrency. Below are a few reason why you should specifically pay attention to the correct implementation of ACID and isolation levels:
- Corruption of Data: In the instance of a newly created transaction in progress, the data could be left in a broken state based upon a partially executed transaction.
- Lost Updates: A transaction could perform a set of actions to make an update to certain data, however if two sets of transactions execute at the same time, it might overwrite one another updates.
- Stale or Inconsistent Reads: Transactions could use outdated or incomplete data to participate in data processes that should have relied on current sanctioned data.
- Deadlocks and Contention: the improper use of isolation levels could result in transactions blocking each other.
By understanding and applying ACID properties, and choosing an appropriate isolation level for your use case, you can build more robust applications that safeguard your data.
Best Practices for Usage
Use Transactions Judiciously
Not every database operation requires a transaction, but you should wrap any multi-step process that modifies data across multiple tables or rows in one.
Minimize Transaction Duration
Long running transactions loosen locks on resources. Holding locks longer increases the chance of creating contention, where one busy resource waits for another. Always aim to do as little work as possible within a transaction and keep the transaction as short as possible.
Create a Recovery Plan For Errors
Incorporate error recovery logic that will allow your application to fail gracefully without leaving the database in a poor state when a failure occurs. You should also ensure that you incorporate rollback logic.
Understand Isolation Levels
Higher isolation levels provide greater consistency, but require greater performance cost. Use the least restrictive isolation level that works for your consistency needs.
Test For Concurrent Usage
Simulate concurrent users in the test phase to ensure that your application handles contention and race conditions.
Conclusion
SQL transactions are a fundamental construct in relational database management that guarantee reliable, consistent and recoverable operations on data. Understanding how ACID properties work and applying the proper isolation levels can help developers and database administrators to build reliable systems with optimal performance.
As your applications grow and you have multiple concurrent users, an understanding of these concepts can help you avoid anomalies in the data, improve stability, and maintain users’ trust.
