BASE properties in distributed databases refer to a set of principles that prioritize availability and partition tolerance over strict consistency. BASE stands for Basically Available, Soft state, and Eventually consistent. This model is often contrasted with the ACID properties, which are essential for traditional transactional databases. While ACID focuses on ensuring that transactions are processed reliably through strong consistency, BASE accepts that in distributed systems, especially those that scale, it is often more practical to allow for some degree of inconsistency for the sake of performance and availability.
Basically Available means that the system guarantees a certain level of availability for the data, even in the event of failures. This does not mean that every query will return the most up-to-date information; rather, the system is designed to continue operating and returning responses as much as possible. For instance, in a distributed system like Amazon’s DynamoDB, if a part of the system goes down, it can still process requests and return data that might not be the absolutely latest but is available nonetheless.
Soft state acknowledges that the state of the system may change over time even without new input. This aspect addresses the nature of distributed systems where data can be replicated across multiple nodes. Changes made on one node may not be immediately reflected on another, creating a temporary inconsistency. Finally, Eventually consistent means that while the data may not be immediately consistent across all nodes, the system ensures that updates will eventually propagate throughout the network, leading to a consistent state over time. An example of this is in systems like Apache Cassandra, where nodes can accept writes independently, and the data eventually converges to consistency through a process of synchronization. This approach allows for higher availability and responsiveness, especially in global applications where latency can be an issue.