Snapshot Isolation vs Read Committed Isolation in Databases

Sep 1, 2023 · 4 min read

Hey everyone, it’s alanturrr1703 back again with another blog post! 😄 Today, we’ll be diving into two important isolation levels in databases—Snapshot Isolation and Read Committed Isolation.

These two terms might sound technical, but they play a huge role in how databases handle concurrent transactions. Whether you’re a developer working with databases or just curious, understanding these isolation levels is key to ensuring data integrity.

Let’s break them down! 📚

What is Isolation in Databases?

First, a quick refresher: Isolation is one of the four ACID properties (Atomicity, Consistency, Isolation, Durability) we talked about in a previous blog. It ensures that multiple transactions can occur simultaneously without affecting each other.

Different isolation levels define how strict or loose the database is about controlling access to data during concurrent transactions. Some allow more freedom for performance, while others prioritize strict consistency.

Let’s focus on two popular isolation levels: Snapshot Isolation and Read Committed Isolation.

Read Committed Isolation

Read Committed is one of the most common isolation levels in databases. Its primary rule is simple: you can only read committed data.

How It Works:

In Read Committed Isolation, a transaction will:

Only read data that has been committed by other transactions. This means that any ongoing transactions’ uncommitted changes are invisible to others.
Hold locks during writing but release them immediately after the write is complete. This reduces blocking other transactions from accessing the data but increases the chance of issues like non-repeatable reads.

Example:

Imagine two transactions occurring simultaneously:

Transaction 1: Updates a product price from ₹100 to ₹120.
Transaction 2: Queries the product price while Transaction 1 is still running.

In Read Committed, Transaction 2 will always see the product price as ₹100 until Transaction 1 commits its changes. Once Transaction 1 commits, Transaction 2 will see the updated ₹120 price.

Pros:

It’s efficient and reduces the overhead of locking.
Prevents dirty reads (reading uncommitted changes from other transactions).

Cons:

It does not prevent non-repeatable reads. This means if Transaction 2 queries the product price twice, it may see different values if Transaction 1 commits between the two reads.
Does not fully protect against phantom reads, where a transaction might see new rows inserted by other transactions during its execution.

Snapshot Isolation

Now, let’s talk about Snapshot Isolation—a more advanced and stricter isolation level. Here, the database takes a snapshot of the data when a transaction begins, and the transaction works on that snapshot throughout its execution.

How It Works:

Reads always come from a consistent snapshot. When a transaction starts, it gets a view of the database at that exact moment. No changes made by other transactions after this point will affect what the transaction reads.
Writes are checked against the latest committed data. If two transactions modify the same row, one of them will fail due to a write conflict.

Example:

Using the same example as above:

Transaction 1 updates the product price from ₹100 to ₹120.
Transaction 2 starts while Transaction 1 is running and queries the product price.

With Snapshot Isolation, Transaction 2 will continue to see the product price as ₹100, even if Transaction 1 commits during its execution. Once Transaction 2 completes, it may either commit its changes or detect a conflict if it tries to modify the same data that was changed by Transaction 1.

Pros:

No dirty reads, no non-repeatable reads, and no phantom reads.
Allows higher consistency than Read Committed Isolation.
Ideal for systems where transactions need to read consistent data throughout their execution.

Cons:

Write conflicts: If two transactions try to write to the same data, one will fail and need to be retried. This can lead to performance hits in write-heavy systems.
More memory and storage are needed to maintain the snapshots.

Key Differences

Let’s break down the key differences between Read Committed and Snapshot Isolation:

Feature	Read Committed Isolation	Snapshot Isolation
Reads committed data	Yes	Yes
Dirty reads	No	No
Non-repeatable reads	Yes	No
Phantom reads	Yes	No
Write conflicts	No	Yes (due to snapshots)
Performance overhead	Low	Higher (due to snapshots)
Consistency	Moderate	High

Which One to Choose?

Both isolation levels have their advantages and trade-offs, and the choice often depends on the needs of your system:

Read Committed Isolation is great for applications that prioritize performance and don’t require perfect consistency. It’s widely used in OLTP (Online Transaction Processing) systems where many users are making quick transactions.
Snapshot Isolation is ideal for systems where consistency is more important, such as in banking or financial applications. It ensures that every transaction sees a stable snapshot of the data, though it might require more memory and careful handling of write conflicts.

Wrapping It Up

Isolation levels are all about finding the right balance between performance and data consistency. While Read Committed Isolation allows for faster reads and less locking, Snapshot Isolation ensures that every transaction works with a consistent view of the database.

I hope this post cleared up the differences between these two isolation levels. Understanding them can really help you design more efficient and reliable database systems.

Until next time, happy coding! 😄