Introduction
Isolation levels in RDBMS transactions determine how much one transaction can see of another transaction’s work, and are used to control the concurrent access of data by multiple transactions. Each isolation level has its own strengths and weaknesses, and it is important to choose the appropriate level based on the requirements of the system.
There are four different isolation levels in RDBMS transactions, which we will explore in more detail below:
Read Uncommitted
Read Uncommitted is the lowest isolation level and allows dirty reads, which means that a transaction can read data that has been modified by another transaction that has not yet been committed. This level provides the highest level of concurrency, but the least data integrity. As a result, it is not commonly used in production environments. An example use case for Read Uncommitted is a reporting system where data accuracy is not critical, and high concurrency is required.
In this isolation level, transactions can read uncommitted changes made by other transactions. It is the lowest level of isolation and offers no protection against dirty reads, non-repeatable reads, and phantom reads. For example, Transaction A reads an uncommitted value modified by Transaction B, but Transaction B aborts or rolls back later. In this case, Transaction A would have read an incorrect value.
Read Committed
Read Committed is the default isolation level for most RDBMSs. It allows a transaction to read only committed data, which eliminates dirty reads. This level provides a good balance between concurrency and data integrity. An example use case for Read Committed is a system where data accuracy is important, but high concurrency is also required, such as an online shopping application.
In this isolation level, a transaction can only read data that has been committed by other transactions. It avoids dirty reads but still allows non-repeatable and phantom reads. For example, Transaction A reads a committed value modified by Transaction B, but Transaction B commits a different value later. In this case, Transaction A would have read an incorrect value.
Repeatable Read
Repeatable Read is a higher isolation level that ensures that a transaction can see the same data throughout the transaction, even if other transactions modify the data. This level provides a higher level of data integrity, but at the cost of concurrency. An example use case for Repeatable Read is a banking application where data consistency is critical, and high concurrency is not as important.
In this isolation level, a transaction can read the same data repeatedly during the transaction’s lifetime. It avoids non-repeatable reads but still allows phantom reads. For example, Transaction A reads a row, then Transaction B inserts a new row with matching criteria. In this case, Transaction A would not see the newly inserted row, resulting in a phantom read.
Serializable
Serializable is the highest isolation level and provides the highest level of data integrity. It ensures that transactions are executed in a serializable manner, as if they were executed one after the other. This level provides the least concurrency and is the slowest isolation level. An example use case for Serializable is a system where data consistency is absolutely critical, such as a financial system that processes transactions.
In this isolation level, transactions are executed serially as if one transaction is executed at a time. It provides the highest level of isolation and avoids dirty reads, non-repeatable reads, and phantom reads. For example, Transaction A reads a row, then Transaction B modifies or deletes the same row before Transaction A finishes. In this case, Transaction A would have been rolled back to maintain serializability.
Choosing the Right Isolation Level
In most of the cases, Read Committed will be the default isolation level that will be required. For rest of the cases, choosing the right isolation level is crucial in ensuring that a database system is both efficient and reliable. When selecting an isolation level, it is important to consider the application’s requirements, including the level of concurrency needed, the importance of data accuracy, and data integrity.