A.1.6 Explain Concurrency in a Data Sharing Situation

Concurrency in a data-sharing situation refers to the ability of multiple users or applications to access and manipulate the same data simultaneously. In database management, concurrency is vital for ensuring efficiency and scalability in shared environments, such as multi-user systems, where numerous processes operate at the same time.

Why Concurrency Matters

Concurrency allows systems to:

1. Improve Efficiency:

   • Multiple tasks or queries can be processed simultaneously, reducing wait times for users.
   • Example: In an online shopping platform, multiple customers can browse products, place orders, and check out concurrently.

2. Enhance Scalability:

   • Systems can handle large numbers of users or operations without degrading performance.

3. Facilitate Collaboration:

   • Teams or applications can access and update shared data in real-time, enabling better collaboration.

Challenges of Concurrency

Concurrency, while beneficial, can lead to issues if not managed properly. These include:

1. Data Conflicts:

   • Multiple users attempt to modify the same data simultaneously.
   • Example: Two customers trying to book the last seat on a flight.

2. Inconsistencies:

   • If two transactions read and modify the same data without proper synchronization, inconsistencies may arise.
   • Example: A user withdraws money from an ATM while the bank updates their balance.

3. Lost Updates:

   • Changes made by one transaction are overwritten by another transaction.
   • Example: Two employees updating the same customer record simultaneously, leading to one update being lost.

4. Deadlocks:

   • Two or more transactions wait indefinitely for resources locked by each other.
   • Example: Transaction A locks account X and waits for account Y, while transaction B locks account Y and waits for account X.

Concurrency Control Mechanisms

To address these challenges, database management systems (DBMS) implement concurrency control techniques:

1. Locking:

   • Prevents multiple transactions from accessing the same resource simultaneously.
   • Example:
     • A transaction locks a record during an update. Other transactions must wait until the lock is released.

2. Time-Stamping:

   • Assigns a unique timestamp to each transaction. Transactions are executed in the order of their timestamps.
   • Example:
     • If two transactions try to update the same record, the one with the earlier timestamp is given priority.

3. Multi-Version Concurrency Control (MVCC):

   • Creates multiple versions of a record so that read operations do not block write operations.
   • Example:
     • While one user reads a version of the record, another user can modify a separate version. The database resolves conflicts at the end.

Example Scenario: Online Shopping

1. Concurrency Challenge:

   • Multiple customers access the same product page for a limited stock item.
   • Customers A and B both try to buy the last remaining item simultaneously.

2. Concurrency Solution:

   • A locking mechanism ensures that when Customer A’s transaction locks the inventory record, Customer B must wait until the lock is released.
   • If Customer A completes the purchase, Customer B is notified that the item is out of stock.