PostgreSQL MVCC: Understanding Multi-Version Concurrency Control in PostgreSQL

PostgreSQL is a very popular open-source object-relational database system that uses a unique approach to handle concurrency called Multi-Version Concurrency Control (MVCC). Let's explore what MVCC is, how it works, and why it is essential for PostgreSQL.

What is Multi-Version Concurrency Control (MVCC)?

MVCC is a concurrency control method used in relational database management systems (RDBMS). It allows multiple transactions to access the same data simultaneously while maintaining data consistency and isolation. It does this by creating multiple versions of a row and allowing each transaction to access its version of the row, rather than locking the entire table or row.

So in this, a transaction does not lock a row and works on its copy or version of row.

How does MVCC work in PostgreSQL?

In PostgreSQL, every row in a table has a hidden transaction ID, called xmin, and a maximum transaction ID, called xmax. The xmin is the transaction ID of the first transaction that inserted the row, while the xmax is the transaction ID of the latest transaction that modified or deleted the row. When a transaction starts, it is assigned a unique transaction ID, and it can only access rows that have a xmin less than or equal to its ID and a xmax greater than its ID.

Write:

When a transaction modifies a row, a new version of the row is created with a new xmax that is equal to the transaction ID of the modifying transaction. The old version of the row remains in the table with its xmax set to the transaction ID of the transaction that created it.

Read:

When a transaction reads a row, it will only see the version of the row that is valid at the time of its transaction ID. This ensures that transactions do not interfere with each other and that each transaction sees a consistent view of the database.

Let's understand with an example

First Read scenario:

Let's say you have a PostgreSQL database with a table called "customers" that contains information about your company's customers. There are two concurrent transactions running at the same time:

• Transaction A: This transaction starts at time T1 and reads the "name" column for customer #1.

• Transaction B: This transaction starts at time T2 and updates the "name" column for customer #1.

In a database that uses a locking-based concurrency control method, Transaction B would need to acquire a lock on the row for customer #1 before it could make any changes. This would prevent Transaction A from reading the row until Transaction B releases the lock, which can cause contention and slow down the system.

However, in a PostgreSQL database that uses MVCC, Transaction A can still read the row for customer #1 even while Transaction B is updating it. This is because PostgreSQL creates a new version of the row for Transaction B to modify, but Transaction A can still see the old version of the row as it existed at the start of its transaction.

So when Transaction A reads the "name" column for customer #1, it sees the value that was there at the start of its transaction, even though Transaction B has updated the row in the meantime. This allows both transactions to proceed concurrently without blocking each other or causing contention.

Now Write Scenario:

Let's say you have a PostgreSQL database with a table called "orders" that contains information about customer orders. There are two concurrent transactions running at the same time:

• Transaction A: This transaction starts at time T1 and updates the "status" column for order #1.

• Transaction B: This transaction starts at time T2 and updates the "quantity" column for order #1.

When Transaction A updates the "status" column for order #1, PostgreSQL creates a new version of the row with the updated value and marks the old version as "dead." This new version of the row is only visible to Transaction A, which can read and modify it without blocking other transactions.

Similarly, when Transaction B updates the "quantity" column for order #1, PostgreSQL creates another new version of the row with the updated value and marks the previous version as "dead." This new version of the row is only visible to Transaction B, which can read and modify it without blocking other transactions.

So when both transactions commit their changes, PostgreSQL applies the new versions of the row for each transaction and makes them visible to other transactions. This allows both transactions to proceed concurrently without blocking each other or causing contention.

Why is MVCC essential for PostgreSQL?

MVCC provides several benefits for PostgreSQL.

Performance: It allows multiple transactions to access the same data simultaneously, which improves performance and scalability.

Concurrency: it provides high levels of concurrency without requiring locks or blocking, which reduces the chance of deadlocks and improves overall system throughput.

Finally, it enables PostgreSQL to support advanced features, such as read-only transactions, snapshot isolation, and online backups.

Trade-offs

The primary trade-off is increased disk space usage. As multiple versions of each row may need to be stored in the database to support MVCC, this can result in a larger database size compared to other concurrency control methods that use locking. This can lead to slower queries and longer backup times, particularly for databases with large tables and high write rates.

Another trade-off is that the increased complexity of MVCC can make it more challenging to optimize queries and diagnose performance issues. Because each transaction has its own snapshot of the database, query plans can be affected by changes to the underlying data over time. This can make it more difficult to predict the performance impact of changes to the database schema or query logic. Additionally, some query optimizations may not work as well with MVCC, as the database needs to consider multiple versions of each row when generating query plans.

Conclusion

MVCC is a powerful concurrency control method that allows PostgreSQL to handle high levels of concurrency while maintaining data consistency and isolation. It achieves this by creating multiple versions of a row and allowing each transaction to access its version of the row, rather than locking the entire table or row. This unique approach to concurrency control provides PostgreSQL with several benefits, including improved performance, scalability, and advanced features. If you're using PostgreSQL, it's essential to understand how MVCC works to ensure that your application performs optimally.

Thanks for reading, your engagements are welcome. In the follow-up article, I will be talking about how PostgreSQL deals with these dead rows created as an outcome of MVCC.