Synchronous and Asynchronous Replication

Last modified: May 11, 2025

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Synchronous and Asynchronous Replication

Replication is an important concept in database systems, involving the copying of data from one database server, known as the primary, to one or more other servers called replicas. This process enhances data availability, fault tolerance, and load balancing across the system. Understanding the two main replication strategies—synchronous and asynchronous replication—is crucial for designing robust and efficient database architectures.

Replication Strategies

At its core, replication ensures that data is consistently available across multiple servers. The key difference between synchronous and asynchronous replication lies in how and when data changes are propagated from the primary server to the replicas.

Synchronous Replication

In synchronous replication, every write operation on the primary database is immediately propagated to the replicas. The primary server waits for acknowledgments from all replicas before confirming the transaction to the client. This means that data is consistent across all servers at any given moment.

How it works:

A client sends a write request to the primary server.
The primary server writes the data and sends the changes to all replicas.
Each replica writes the data and sends an acknowledgment back to the primary server.
Once all acknowledgments are received, the primary server confirms the transaction to the client.

Client
  |
  | (1) Write Request
  v
+--------------------+
|   Primary Server   |
+---------+----------+
          |
          | (2) Send Data to Replicas
          v
+---------+----------+       +---------+----------+
|    Replica 1       |       |    Replica 2       |
+---------+----------+       +---------+----------+
          | (3) Ack                    | (3) Ack
          +-----------+----------------+
                      |
             (4) Confirm Transaction
                      |
                      v
        Transaction Confirmed to Client

Advantages	Disadvantages
Ensures strong data consistency across all servers	Increases latency because the primary server waits for acknowledgments from replicas
Minimizes the risk of data loss since data is committed on all servers before confirmation	May impact performance, especially in environments with high network latency
Simplifies failover processes because replicas are always up-to-date	Scalability can be limited due to the overhead of maintaining synchronization

Asynchronous Replication

Asynchronous replication allows the primary server to confirm transactions without waiting for replicas to acknowledge the data writes. Data changes are sent to replicas after the transaction has been committed on the primary server, which means there may be a delay before replicas are updated.

How it works:

A client sends a write request to the primary server.
The primary server writes the data and immediately confirms the transaction to the client.
The primary server queues the data changes for replication.
Replicas receive the data changes asynchronously and update their data.

Client
  |
  | (1) Write Request
  v
+--------------------+
|   Primary Server   |
+---------+----------+
          | (2) Immediate ACK to Client
          |
          | (3) Send Data to Replicas
          v
+---------+----------+       +---------+----------+
|    Replica 1       |       |    Replica 2       |
+---------+----------+       +---------+----------+
          | (4) ACK                    | (4) ACK
          +-----------+----------------+
                      |
             [Replication Complete]

Advantages	Disadvantages
Reduces latency since the primary server doesn't wait for replicas	Potential for data inconsistency between the primary and replicas
Improves performance and throughput on the primary server	Risk of data loss if the primary server fails before replication occurs
More scalable in environments with high network latency or geographically distributed replicas	More complex failover procedures may be required to ensure data integrity

Choosing Between Synchronous and Asynchronous Replication

Selecting the appropriate replication strategy depends on the specific needs of your application and infrastructure.

Category	Synchronous Replication	Asynchronous Replication
Data Consistency	Strong—writes are confirmed only once all replicas have committed, ensuring identical data across nodes.	Eventual—primary confirms writes immediately; replicas catch up afterward, so briefly divergent states are possible.
Latency Impact	Higher—each transaction waits for replica acknowledgments, adding round-trip delays.	Lower—primary does not wait, so transactions complete as soon as local commit is done.
Throughput & Performance	Moderate—overall throughput can suffer under high-load or high-latency conditions due to synchronization overhead.	High—primary server can handle more transactions per second without waiting on replicas.
Scalability	Limited—scaling to many or geographically distant replicas exacerbates latency and coordination costs.	Excellent—replicas can be added anywhere without significantly affecting primary performance.
Failover Complexity	Simple—since replicas are up-to-date, promoting one to primary is straightforward.	Complex—need to detect and reconcile any unreplicated transactions; risk of data loss on failover.
Risk of Data Loss	Minimal—as long as a majority (or all, depending on quorum) of replicas acknowledge, data is safe.	Present—writes acknowledged by primary may not yet exist on replicas if a sudden failure occurs.
Typical Use Cases	● Financial transaction systems ● Order-entry platforms ● Catalog updates requiring atomicity	● Global content distribution ● Analytics or logging pipelines ● High-performance web applications where slight lag is acceptable
Best Network Conditions	Low-latency, high-bandwidth links (e.g., within the same data center or region).	Variable or high-latency networks (e.g., cross-continent, multi-cloud or edge deployments).

Best Practices

Implementing replication effectively requires careful planning and consideration of several factors.

Application Requirements:

Assess the criticality of data consistency versus performance needs.
Determine acceptable levels of latency and potential data loss.
Plan for failure scenarios and how the system should respond.

Monitoring and Maintenance:

Regularly monitor replication status and lag times.
Set up alerting mechanisms for replication failures or significant delays.
Perform routine testing of failover procedures.

Optimizing Network Infrastructure:

Ensure reliable, high-speed network connections between servers.
Use network optimization techniques to reduce latency.
Consider network security measures to protect data during replication.

Data Safety Measures:

Maintain regular backups, even when using replication.
Implement transaction logging to assist with recovery if needed.
Periodically validate data consistency between the primary and replicas.