Data Replication using sync and async mode

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### Data Replication Overview

Data replication means copying data from one main source (the "master") to other locations ("replicas") to make it accessible across multiple systems or locations. This helps with data availability and reliability, especially in distributed systems. Here’s how it works differently in **synchronous**, **asynchronous**, and **semi-synchronous** scenarios.


### Synchronous Replication

1. **Process**:

   - When a client writes (or sends) data to the master, the master saves it to its own storage.

   - Then, the master **sends this data to all replicas**.

   - **Only after all replicas confirm** that they have received and saved the data, the master tells the client the write is successful.


2. **Consistency**:

   - This guarantees that all copies of the data are **exactly the same** at all times.

   - If one replica fails to receive the data, the client gets an error, meaning the write didn’t complete everywhere.


3. **Downside**:

   - Because the master waits for each replica to confirm, the operation’s speed depends on the **slowest replica**. This can introduce **delays** due to network latency or slow storage on one of the replicas.

   - If any replica is down, the master may stop accepting writes entirely, only allowing read operations.


4. **Example in Real Life**:

   - Think of synchronous replication like a group decision where everyone in a team has to agree before moving forward. If one person (replica) is slow to respond, everyone else has to wait.


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### Asynchronous Replication

1. **Process**:

   - When a client writes data to the master, the master immediately saves it and **notifies the client that the write was successful**.

   - After that, the master starts copying this data to the replicas **in the background**, without making the client wait for confirmation from each replica.


2. **Consistency**:

   - The replicas will eventually receive the data, but there’s no guarantee that they all have the **latest version immediately**.

   - If the master fails before the replicas receive the data, some replicas might not get it at all, which can lead to data loss.


3. **Upside**:

   - **Faster write operations** since the master doesn’t wait for each replica to confirm. The client gets a quick response, making it ideal for systems needing high-speed writes.


4. **Downside**:

   - There’s a risk of data inconsistency. If a failure occurs, some replicas may not have the latest data.

   

5. **Example in Real Life**:

   - Imagine sending an email where you don’t expect an immediate reply. You send it off, and the person reads it whenever they get the chance, so the communication isn’t “instant” on both ends.


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### Semi-Synchronous Replication

1. **Process**:

   - This method is a **hybrid** of synchronous and asynchronous replication.

   - When the client writes data to the master, the master waits for **at least one replica to confirm** that it received the data.

   - Once at least one replica confirms, the master notifies the client that the write is successful.

   - The remaining replicas receive the data asynchronously, meaning they may take longer.


2. **Consistency**:

   - This approach balances speed and reliability by waiting for at least one confirmation, ensuring that at least one replica has the latest data if something goes wrong.

   - Other replicas will eventually catch up but may not have the latest version immediately.


3. **Upside**:

   - Semi-synchronous replication provides **better speed than full synchronous** (since only one replica needs to respond) and **more reliability than asynchronous** (since at least one replica has the data immediately).


4. **Downside**:

   - There’s still a chance that some replicas might be outdated for a short period, so data might not be fully consistent across all replicas.


5. **Example in Real Life**:

   - Think of it like making sure one team member acknowledges a decision before moving on, knowing the others will catch up soon. This provides a balance between waiting for everyone and waiting for no one.


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### Summary of Each Replication Type


- **Synchronous**: The client waits for all replicas to confirm. High consistency, but can be slow.

- **Asynchronous**: The client doesn’t wait. Fast, but replicas may not always be up-to-date.

- **Semi-Synchronous**: The client waits for one replica to confirm. Balanced between speed and consistency.


These examples should help you understand each method's strengths and weaknesses. Let me know if you need further clarification on any part!

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