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Isolation

Most databases are accessed by several clients at the same time. That is no problem if they are reading and writing different parts of the database, but if they are accessing the same database records, you can run into concurrency problems (race conditions).

Figure 7-1 is a simple example of this kind of problem. Say you have two clients simultaneously incrementing a counter that is stored in a database. Each client needs to read the current value, add 1, and write the new value back (assuming there is no increment operation built into the database). In Figure 7-1 the counter should have increased from 42 to 44, because two increments happened, but it actually only went to 43 because of the race condition.

Isolation in the sense of ACID means that concurrently executing transactions are isolated from each other: they cannot step on each other’s toes. The classic database textbooks formalize isolation as serializability, which means that each transaction can pretend that it is the only transaction running on the entire database. The database ensures that when the transactions have committed, the result is the same as if they had run serially (one after another), even though in reality they may have run concurrently [10].

A race condition between two clients concurrently incrementing a counter

Figure 7-1. A race condition between two clients concurrently incrementing a counter.

However, in practice, serializable isolation is rarely used, because it carries a performance penalty. Some popular databases, such as Oracle 11g, don’t even implement it. In Oracle there is an isolation level called “serializable,” but it actually implements something called snapshot isolation, which is a weaker guarantee than serializability [8, 11]. We will explore snapshot isolation and other forms of isolation in “Weak Isolation Levels” on page 233.

 
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