  Read-only caches are widely used in cloud infrastructures to reduce access
latency and load on backend databases. Operators view coherent caches as
impractical at genuinely large scale and many client-facing caches are updated
in an asynchronous manner with best-effort pipelines. Existing solutions that
support cache consistency are inapplicable to this scenario since they require
a round trip to the database on every cache transaction.
  Existing incoherent cache technologies are oblivious to transactional data
access, even if the backend database supports transactions. We propose T-Cache,
a novel caching policy for read-only transactions in which inconsistency is
tolerable (won't cause safety violations) but undesirable (has a cost). T-Cache
improves cache consistency despite asynchronous and unreliable communication
between the cache and the database. We define cache-serializability, a variant
of serializability that is suitable for incoherent caches, and prove that with
unbounded resources T-Cache implements this new specification. With limited
resources, T-Cache allows the system manager to choose a trade-off between
performance and consistency.
  Our evaluation shows that T-Cache detects many inconsistencies with only
nominal overhead. We use synthetic workloads to demonstrate the efficacy of
T-Cache when data accesses are clustered and its adaptive reaction to workload
changes. With workloads based on the real-world topologies, T-Cache detects
43-70% of the inconsistencies and increases the rate of consistent transactions
by 33-58%.
