An SQL database must handle multiple incoming connections simultaneously to maintain optimal system performance. The expectation is that the database can accept and process numerous requests in parallel. It’s straightforward when different requests target separate data, such as one request reading from Table 1 and another from Table 2. However, complications arise when multiple requests involve reading from and writing to the same table. How do we keep the performance high and yet avoid consistency issues? Let’s read on to understand how things work in SQL databases and distributed systems.

Transactions and Issues

An SQL transaction is a collection of queries (such as SELECT, INSERT, UPDATE, DELETE) sent to the database to be executed as a single unit of work. This means that either all queries in the transaction must be executed, or none should be. Executing transactions is not atomic and takes time. For example, a single UPDATE statement might modify multiple rows, and the database system needs time to update each row. During this update process, another transaction might start and attempt to read the modified rows. This raises the question: should the other transaction read the new values of the rows (even if not all rows are updated yet), the old values of the rows (even if some rows have been updated), or should it wait? What happens if the first transaction must be canceled later for any reason? How should this affect the other transaction?

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