1. Non-repeatable reads: In a Read Committed isolation level, a transaction may read the same data multiple times and get different results if another transaction updates the data in between reads. This can lead to inconsistency in data.

To fix this issue, you can use locking mechanisms such as row-level locks or table-level locks to prevent other transactions from updating the data while it is being read by another transaction.

2. Phantom reads: Phantom reads occur when a transaction reads a set of rows that satisfy a certain condition, but another transaction inserts or deletes rows that also satisfy the condition, causing the first transaction to see additional or missing rows.

To fix this issue, you can use range locks or index locks to prevent other transactions from inserting or deleting rows that would affect the result set of the first transaction.

3. Performance impact: Read Committed isolation level may lead to performance issues in highly concurrent environments due to locking mechanisms used to prevent dirty reads.

To improve performance, you can consider using optimistic concurrency control techniques such as timestamp-based validation or snapshot isolation to allow multiple transactions to read and write data concurrently without blocking each other.

4. Deadlocks: In a Read Committed isolation level, multiple transactions may acquire locks on different resources in a way that each transaction is waiting for a resource held by another transaction, leading to a deadlock situation where none of the transactions can proceed.

To avoid deadlocks, you can design your application to acquire locks in a consistent order or use deadlock detection and resolution mechanisms to automatically resolve deadlock situations by rolling back one of the transactions involved.

5. Inconsistent query results: Read Committed isolation level may result in inconsistent query results if the data being read is being updated by other transactions at the same time.

To ensure consistent query results, you can use explicit transactions with appropriate locking mechanisms and ensure that transactions are committed in a consistent order to avoid data inconsistencies.

The concept of Read Committed was first introduced in the early 1980s as a way to address the issue of dirty reads in database systems. It was a significant development in the field of transaction isolation levels, as it allowed for improved data consistency without sacrificing too much in terms of performance. Over the years, Read Committed has become a widely used standard in database management systems, demonstrating its effectiveness in ensuring data integrity in multi-user environments.