The replication approaches we have discussed so far in this topic—single-leader and multi-leader replication—are based on the idea that a client sends a write request to one node (the leader), and the database system takes care of copying that write to the other replicas. A leader determines the order in which writes should be processed, and followers apply the leader’s writes in the same order.
Some data storage systems take a different approach, abandoning the concept of a leader and allowing any replica to directly accept writes from clients. Some of the earliest replicated data systems were leaderless, but the idea was mostly forgotten during the era of dominance of relational databases. It once again became a fashionable architecture for databases after Amazon used it for its in-house Dynamo system in 2007. Riak, Cassandra, and ScyllaDB are open source datastores with leaderless replication models inspired by Dynamo, so this kind of database is also known as Dynamo-style.
Note
The original Dynamo system architecture was described in a paper but never released outside of Amazon. The similarly named DynamoDB, a more recent cloud database from Amazon, has a completely different architecture: it uses single-leader replication based on the Multi-Paxos consensus algorithm.
In some leaderless implementations, the client directly sends its writes to several replicas, while in others, a coordinator node does this on behalf of the client. However, unlike a leader database, that coordinator does not enforce a particular ordering of writes. As we shall see, this difference in design has profound consequences for the way the database is used.