Transaction processing in DBMS

Transaction processing is like running a busy bank — many people are accessing the system, transferring money, depositing, withdrawing, and it’s important that everything stays accurate and safe, even if something goes wrong (like a power cut).

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1. Concurrency Control

What it is:
Allows many users to use the database at the same time without interfering with each other.

Real-life example:
Imagine a shopping website where two people are trying to buy the last piece of a product at the same time. The database must ensure only one person gets it.

Analogy:
Think of a supermarket checkout. Even if many people shop at once, the system manages them one at a time at the counter so billing is correct.

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2. ACID Properties

ACID ensures that every transaction is processed correctly and safely.

• Atomicity (All or nothing): If you transfer ₹1000 from Account A to B, and the system crashes after taking the money from A but before adding to B, it should undo the transaction.

✅ Real-life example: ATM fails after debiting money — your balance should not reduce.

• Consistency: The database should always follow its rules.

✅ Example: A bank rule says balance can’t go below ₹0. If a transaction tries to break it, it’s denied.

• Isolation: Your transaction works as if it’s the only one running, even when many are.

✅ Example: If two friends are booking the same train seat at the same time, only one gets it.

• Durability: Once a transaction is done, it stays done, even after a crash.

✅ Example: You get a message “Order confirmed” – it should still show in your order history even if the system restarts.

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3. Serializability of Scheduling

What it is:
It ensures transactions give the same result as if they were done one by one, even if they run together.

Real-life example:
Two chefs work in the same kitchen. If they don’t follow proper order, dishes might mix up. The goal is to make sure each dish is cooked properly as if only one chef was in the kitchen.

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4. Locking and Timestamp-Based Schedulers

🔒 Locking:

What it is:
Stops two people from changing the same data at the same time.

Example:
When you edit a Google Doc, others can’t type in the same place — it’s "locked" to prevent a clash.

• Read Lock: You can see the data, but not change it.
• Write Lock: You are the only one who can change it.

⏱ Timestamp:

What it is:
Each transaction gets a time number. The older one gets priority to avoid conflicts.

Example:
Like in a bakery — people get tokens. Whoever got the token earlier is served first.

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5. Multi-Version and Optimistic Concurrency Control

Multi-Version Control:

What it is:
Keeps multiple copies (versions) of data for reading, so reading doesn’t block writing.

Example:
While your friend edits a document, you can still read the old version.

Optimistic Concurrency Control:

What it is:
Assumes no conflict will happen, and checks at the end if everything’s okay.

Example:
If you and your friend edit different parts of a shared doc, it works. But if you both change the same sentence, it asks: “Which one to keep?”

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6. Database Recovery

What it is:
Restores the database to a good state if something goes wrong (like a crash or power failure).

Real-life example:
You’re writing a school project and your laptop crashes — but autosave brings your file back!

Methods Used:

• Log-based recovery: Like a diary that tracks every step, so it can redo or undo actions.
• Checkpoints: Save points in the system, like a game save — if crash happens, it can restart from there.

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🎯 Summary Table

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Thanks for reading .