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The isolation feature is required for multiuser databases When there is more than one person modifying data in a database, odd things can happen If two people attempt to modify the same data value at the same time, who is to say which value is the final value
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When more than one person attempts to access the same data, the DBMS must act as a traffic cop, directing who gets access to the data first Isolation ensures that each transaction in progress is invisible to any other transaction that is in progress The DBMS must allow each transaction to complete, and then decide which transaction value is the final value for the data This is accomplished by a technique called locking Locking does what it says; it locks data while a transaction is being committed to the database While the data is locked, other users are not able to access the data, not even for queries This prevents multiple users from querying or modifying the data while it is in a locked mode There are two basic levels of locking that can be performed on table data: Table-level locking Record-level locking Early DBMS implementations used table-level locking Any time a user required a modification to a record in a table, the entire table was locked, preventing other users from even viewing data in the table In some database implementations the lock produces an error event, while in others, the database engine just waits its turn in line to access the data It s not hard to see that this method has its limitations In a multiuser environment, it would be frustrating to be continually locked out of your database table while updates were being made by other users To help solve the table-level locking problem, most modern DBMS packages use record-level locking This method allows access to most of the table; only the record that contains the value being modified is locked The rest of the table is available for other users to view and even modify Although using record-level locking helps, it still does not solve the problem of when two users want to modify the same data at the same time PostgreSQL, however, takes record locking a step further PostgreSQL uses a technique called Multiversion Concurrency Control (MVCC) MVCC uses a sophisticated locking system that, to the user, does not appear to lock records at all To accomplish this, PostgreSQL maintains multiple versions of records that are being updated If an update is made to a record that is currently in use, PostgreSQL keeps the new (updated) version of the record on hold, allowing queries to use the current version of the record When the record becomes available, PostgreSQL applies the new version to the record, updating the table If multiple updates are being made on a record, PostgreSQL keeps each version on hold, and applies the latest version to the record To users and application programs, at least some version of the record is always available This feature in itself allows for other features to be included in PostgreSQL Since no records are ever locked, a backup copy of any table can be made without stopping the DBMS This technique is called online backups (also called hot backups) It ensures that every database backup contains a copy of every record in the table, even the ones currently in use Not having to take a database down for backups is a great feature for highdemand production environments that do business 24 hours a day
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The durability feature is a must for a modern-day DBMS It states that once a transaction is committed to the database, it must not be lost While this sounds like a simple concept, in reality durability is often harder to ensure than it sounds Durability means being able to withstand both hardware and software failures A database is useless if a power outage or server crash compromises the data stored in the database The basic feature for durability is obviously good database backups As was mentioned in the Isolation section, PostgreSQL allows administrators to back up databases at any time without affecting users However, databases are usually only backed up once a day, so what about protecting transactions that occur during the day If a customer comes into the store in the morning to order a new laptop, you wouldn t want to lose that information if the database server crashes that afternoon before the evening backup While it is impossible to account for every type of disaster, PostgreSQL does its best to prepare for them To solve this situation, every transaction that operates on the database is placed into a separate log file as the database engine processes it This is demonstrated in Figure 1-6
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