Handling Concurrent Updates in MySQL InnoDB with Sequelize: Transaction Isolation and Row Locks

Problem

When multiple concurrent transactions update the same row, and each update is calculated based on the row's value before the update, the final data can become inconsistent.

Transaction and Lock Overview

MySQL itself does not implement transactions; they are provided by the InnoDB storage engine. InnoDB defines four isolation levels:

1. READ_UNCOMMITTED : Allows dirty reads; the lowest isolation level.

2. READ_COMMITTED : Prevents dirty reads but can produce non‑repeatable reads when one transaction updates a row while another reads it.

3. REPEATABLE_READ : Guarantees that reads within the same transaction return the same data, but phantom reads may still occur; this is the default level.

4. SERIALIZABLE : The highest isolation level, eliminating the above anomalies by forcing transactions to execute as if they were serial.

InnoDB also provides two lock types:

1. Shared lock (read lock) : Allows multiple transactions to read the row concurrently but prevents any of them from writing.

2. Exclusive lock (write lock) : Allows the locking transaction to read and write the row, while other transactions are blocked from acquiring any lock on that row until the lock is released.

Sequelize Example

The recommended solution is to use the SERIALIZABLE isolation level and acquire an exclusive lock on the row. The following async/await code (illustrative only) shows how to start a transaction, set the isolation level, and lock the target row before performing the update.

Note: The actual Sequelize model definition is omitted for brevity.

Important Consideration

When using an exclusive lock, if the query does not use a primary key or indexed column, MySQL may acquire a table‑level lock, severely impacting read/write performance. Therefore, always lock rows via their primary key or an indexed column to ensure row‑level locking.

Conclusion

Besides solving the issue at the database layer with proper isolation and locking, another approach is to serialize the conflicting operations at the application level. The article also raises a question about how concurrent transactions behave under PM2’s cluster mode.