Eventual Consistency
Eventual consistency is a relaxation of the strong-consistency guarantee: writes propagate asynchronously across replicas, and readers may briefly observe stale state, but the system converges to a single value if writes stop. The CAP-theorem trade-off is throughput and availability under partition. TantraDev uses eventual consistency knowingly — never as a side effect — and always with a documented staleness window.
Concepts that travel with this one.
Architecture rarely lives in isolation — these are the terms that come up in the same conversation.
CQRS
Command Query Responsibility Segregation (CQRS) splits the write model from the read model. Commands mutate state through a narrow validated path; queries read from projections optimised for the access pattern. The benefit is independently scalable reads and writes, plus the freedom to denormalise reads aggressively. The cost is two models and the synchronisation between them.
CAP Theorem
The CAP theorem (Brewer) states that a distributed datastore can guarantee at most two of: Consistency, Availability, and Partition tolerance. Since network partitions are inevitable in real systems, the practical trade-off in any production design is between consistency and availability. Saying 'we are CP' or 'we are AP' is an architectural commitment, not a slogan — it dictates retry, replication, and failover behaviour.
Building a system where Eventual Consistency is the load-bearing decision?
30 minutes on the phone, one page in your inbox — what to build, what to skip, what it will cost. You keep the audit even if we are not the right fit.