How do databases manage large-scale transactions?

Databases manage large-scale transactions through techniques like partitioning, indexing, concurrency control, and distributed transactions.

To handle large-scale transactions, databases often use a technique called partitioning. Partitioning involves dividing a database into several parts, which can be stored on different servers. This allows for parallel processing, where multiple transactions can be processed at the same time, significantly increasing the speed and efficiency of the database. Partitioning can be done in several ways, such as range partitioning, where data is divided based on a certain range of values, or hash partitioning, where a hash function is used to distribute the data evenly across multiple partitions.

Another technique used is indexing. An index is a data structure that improves the speed of data retrieval operations on a database. It works in a similar way to an index in a book, allowing the database to find data without having to search every row in a database table every time a database table is accessed. Indexes can be created using one or more columns of a database table, providing the basis for both rapid random lookups and efficient access of ordered records.

Concurrency control is also crucial in managing large-scale transactions. This is the process of managing simultaneous operations on a database so that they do not interfere with each other. Concurrency control ensures the consistency and isolation of transactions, meaning that each transaction is executed as if it is the only operation in the system. This is achieved through techniques such as locking, where a transaction locks the data it is using until it is finished, and timestamping, where each transaction is given a timestamp to determine the order of operations.

Finally, distributed transactions are used when a transaction involves multiple databases. This is a complex process that requires careful coordination to ensure that all parts of the transaction are completed successfully or that the transaction is fully rolled back in the event of a failure. This is typically managed through a two-phase commit protocol, where all the databases involved in the transaction agree to commit the transaction before it is actually committed. This ensures that all databases are kept in sync and that the integrity of the data is maintained.