Eventual consistency is a model of data consistency whereby data is eventually consistent if it eventually converges to one consistent value, regardless of the order in which writes to that data are processed.
Eventual consistency is often used in distributed systems where it is infeasible or impossible to guarantee immediate consistency. In an eventually consistent system, there is no guarantee that a read will return the most recent write. Instead, the system is only guaranteed to return a value that is equal to or newer than the value that was written.
Eventual consistency is often used in conjunction with other consistency models, such as read-after-write consistency or write-after-write consistency, to provide a more comprehensive guarantee of data consistency.
What is eventual consistency vs strong consistency?
Eventual consistency is a type of consistency model used in distributed systems, which allows for some level of inconsistency to exist in the system while guaranteeing that, given enough time, the system will eventually converge to a consistent state.
Strong consistency is a type of consistency model used in distributed systems, which requires that all nodes in the system see the same data at the same time.
What are different types of eventual consistency?
There are many different types of eventual consistency, but the two most common are last-writer-wins (LWW) and read-your-writes (RYW).
LWW is the most common form of eventual consistency. In this model, when two users write to the same data item, the user who writes last is the one whose write "wins". The other user's write is not lost, but it is not visible to other users. This can lead to some confusion, because it is not always clear which write happened first.
RYW is a weaker form of eventual consistency, in which a user can only see their own writes. This means that if two users write to the same data item, each user will only see their own write. The other user's write will be invisible to them. This can lead to some inconsistency, because it is possible for two users to have different views of the data.
Why NoSQL is eventual consistency?
NoSQL databases are designed to provide high availability and scalability, which generally requires sacrificing some level of consistency. In an eventually consistent system, writes may not be immediately visible to all readers, but eventually they will be.
Eventual consistency is a trade-off that allows NoSQL databases to provide high availability and scalability, at the expense of some level of consistency.
Is Kafka eventual consistency?
Kafka is a distributed streaming platform that is used to build real-time data pipelines and streaming applications. It is a highly scalable messaging system that enables you to publish and subscribe to messages in order to process and store them.
Kafka is said to be eventually consistent because it guarantees that all messages will be delivered, but it does not guarantee that they will be delivered in the order in which they were sent. This means that if you have two messages, A and B, that are sent to the same topic, there is no guarantee that message A will be delivered before message B. However, Kafka will eventually deliver both messages. Why is eventual consistency used? Eventual consistency is a data model where reads may not return the most up-to-date write. Eventual consistency is often used in distributed systems where it is not possible or practical to guarantee strong consistency. Eventual consistency guarantees that if no new updates are made to the data, eventually all reads will return the most recent write.