PostgreSQL MVCC Explained (Simply!)

How PostgreSQL handles concurrent reads and writes without locks

I recently learned about PostgreSQL’s MVCC (Multi-Version Concurrency Control), and I’m blown away. Here’s a quick breakdown of what I’ve learned and why it’s so cool.

Some Background

In databases, we perform CRUD operations — Create, Read, Update, and Delete.

• Create, Update, Delete → change the state of the database.

• Read → only queries existing data, without modifying it.

Multiple reads can safely run in parallel, since they don’t affect each other.

But once you start mixing reads and writes, things can get tricky. This is because of race conditions.

How Databases Normally Handle This: Locks

The traditional solution is locking.

• Reads: multiple read operations can safely run in parallel.

• Writes: when a transaction wants to update or delete data, the database places a lock on the affected row (or sometimes the entire table).

• While the lock is in place, other transactions can’t modify (and sometimes can’t even read) that same data.

• Once the write finishes, the lock is released, and other operations continue.

This ensures consistency, but creates a bottleneck:

• Locks serialize operations, which means transactions often wait on each other.

• On busy systems, this becomes a performance bottleneck.

MVCC: PostgreSQL’s Answer

PostgreSQL solves this with MVCC (Multi-Version Concurrency Control).

The idea:

• Reads never block writes.

• Writes never block reads (with a few exceptions).

How? By keeping multiple versions of a row and giving each transaction its own snapshot of the database.

What’s a Snapshot?

Think of a snapshot as a photograph of the database at a given moment in time.

When your transaction starts:

• PostgreSQL captures which rows are “visible” to you at that instant.

• No matter how many writes or deletes happen afterward, your transaction continues to see the database as it was when it began

How it Works

Every row in PostgreSQL has two hidden system columns:

• xmin → ID of the transaction that created the row.

• xmax → ID of the transaction that deleted (or will delete) the row.

When you update or delete a row:

• PostgreSQL doesn’t overwrite it.

• It creates a new version of the row (with a new xmin) and marks the old one as outdated (by setting xmax).

When a transaction begins:

• PostgreSQL takes a snapshot of the database.

• That snapshot records which transactions were active and which were already committed.

• A row is visible to your query if:

  • Its xmin (creator) was committed before your snapshot, and

  • Its xmax (deleter) is either not set, or belongs to a transaction that hasn’t committed yet.

In other words, you always see a stable, consistent view of the database, no matter what concurrent transactions are doing.

Why It’s Awesome

• Fast reads: queries never wait on writers.

• Safe writes: transactions can update without corrupting ongoing reads.

• Consistency: every transaction sees a stable snapshot of the data.

The tradeoff:

• Postgres keeps multiple row versions alive until they’re cleaned up.

• This cleanup happens with VACUUM, which reclaims space from old row versions.

Conclusion

MVCC represents a fundamental shift in how databases handle concurrency. Rather than forcing transactions to wait in line through locks, PostgreSQL allows them to work with their own consistent view of the data simultaneously. This elegant solution transforms what was traditionally a serialization bottleneck into a highly concurrent system.

While MVCC isn't without costs—the storage overhead and need for regular maintenance through VACUUM—these trade-offs are generally worthwhile for most applications. The ability to serve fast, consistent reads while handling concurrent writes makes PostgreSQL particularly well-suited for read-heavy workloads and applications requiring high availability.