![]() This makes CRDTs a form of eventual consistency. This means that to implement better resilience in your system you will need to account for the possibility of prolonged moments where the system has not yet been not fully synchronized. All replicas in the same CRDT database will constantly sync their state to provide as consistent a view of the dataset as possible, but keep in mind that CRDTs are also useful for ensuring high availability in case of network partitions. This situation, albeit normally brief, is the reason why CRDT data structures must hardcode conflict-resolution strategies. ![]() While eventually all replica nodes will converge to the same final state, in the short term a command sent to ReplicaEU may not have yet been propagated to ReplicaUS, for example. The second rule is sometimes referred to as the “observed remove” rule, meaning that you can delete only items that you were able to observe when the command was issued.Ī note on replication lag and consistency model Deleting works only on elements that the replica executing the command has already seen.In a Redis Enterprise CRDT-enabled database, sets operations work under a few additional rules, the two most important of which get applied when merging operations coming from different nodes: This approach offers significant advantages for geo-distributed applications and achieving data consistency. The downside is that the “ replication lag” is also experienced when writing to a value. This enables you to write genuinely geo-distributed applications. In a CRDT database, all replica nodes can independently apply changes to the “fruits” key. Running the same commands in a CRDT-enabled Redis Enterprise database would display the same behavior, but what’s happening behind the scenes is completely different. ![]() Here’s how it looks like when calling actual Redis commands: ![]() Redis Sets are similar to what your favorite programming language offers in the standard library, offering specialized operations to add and remove elements, check if an element is part of the set, and perform set intersection, union, and difference. Let’s look at a Redis data structure with a CRDT equivalent and the nuances that Active-Active geo-distributed replication adds. To ensure that conflicts never happen (there is no concept of conflict resolution) and cause problems in your applications, operations on CRDT data types have to respect a specific set of algebraic properties.ĬRDTs work in Redis Enterprise when you create a CRDT-enabled database because standard commands get swapped with an equivalent CRDT implementation. So how do you develop an Active-Active geo-distributed cluster? Introduction to Conflict -Free Replicated Data Types (CRDTs)Ĭonflict-free replicated data types (CRDTs) (aka convergent replicated data type or commutative replicated data type) are a family of replicated data types with a common set of properties that enable operations to always converge to a final state consistent among all replicas. For write-heavy applications, that’s not enough. Placing read replicas closer to your users is the right thing to enable real-time response. Active-Active Geo-Distribution allows you to place your Redis database cluster instances and data centers close to your users, no matter where they are.
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