Summary of Replication Techniques
Replication is a key strategy in distributed systems to enhance availability, fault tolerance, and scalability. There are several replication techniques, each with its own set of trade-offs. Here’s a summary of the main replication techniques, along with their pros and cons, and real-world examples:
1. Leader-Based Replication
Description:
- A single leader node handles all write requests and propagates changes to follower nodes.
- Followers handle read requests and apply changes received from the leader.
Pros:
- Strong consistency as writes are coordinated through the leader.
- Simple conflict resolution as only the leader handles writes.
Cons:
- Single point of failure: if the leader fails, write operations are temporarily halted until a new leader is elected.
- Can become a bottleneck if the leader is overwhelmed with write requests.
Examples:
- Databases: MySQL with InnoDB, PostgreSQL, Amazon RDS
- Applications: Financial systems, inventory management where strong consistency is critical.
2. Multi-Leader Replication
Description:
- Multiple leaders handle write requests and replicate changes to each other.
- Each leader serves a specific set of clients, and changes are asynchronously propagated to other leaders.
Pros:
- Improved write availability as multiple leaders can handle write requests.
- Useful for geo-distributed setups where leaders are closer to their clients.
Cons:
- Write Conflicts : Resolution is complex due to concurrent writes to different leaders.
- Potential for data inconsistencies if writes are not properly coordinated.
Examples:
- Databases: Active-Active PostgreSQL, Multi-Master MySQL
- Applications: Collaborative editing tools, multi-region web applications.
3. Leaderless Replication
Description:
- All nodes can accept read and write requests.
- Consistency is achieved through quorum mechanisms, where a majority of nodes must agree on an operation.
Pros:
- High availability and fault tolerance as there is no single point of failure.
- Scales well with the number of nodes.
Cons:
- Potential for inconsistencies due to concurrent writes and network partitions.
- Conflict resolution can be complex and might require additional mechanisms.
Examples:
- Databases: Amazon DynamoDB, Cassandra, Riak
- Applications: Social media platforms, content delivery networks, IoT applications.
4. Chain Replication
Description:
- Nodes are organized in a chain where writes are passed down the chain, and reads are performed at the tail of the chain.
- Ensures that writes are replicated in order.
Pros:
- Strong consistency and linearizability.
- Efficient for workloads with heavy writes and fewer reads.
Cons:
- Write latency can be high due to the sequential nature of the replication.
- If any node in the chain fails, it can disrupt the replication process.
Examples:
- Databases: Apache HBase
- Applications: High-throughput data processing applications, logging systems.