Databases can provide scalability by partitioning data across several servers. However, multi-partition, multi-operation transactional access is often expensive, employing coordination-intensive locking, validation, or scheduling mechanisms. Accordingly, many real- world systems avoid mechanisms that provide useful semantics for multi-partition operations. This leads to incorrect behavior for a large class of applications including secondary indexing, foreign key enforcement, and materialized view maintenance. In this work, we identify a new isolation model—Read Atomic (RA) isolation—that matches the requirements of these use cases by ensuring atomic vis- ibility: either all or none of each transaction’s updates are observed by other transactions. We present algorithms for Read Atomic Multi- Partition (RAMP) transactions that enforce atomic visibility while offering excellent scalability, guaranteed commit despite partial failures (via synchronization independence), and minimized com- munication between servers (via partition independence). These RAMP transactions correctly mediate atomic visibility of updates and provide readers with snapshot access to database state by using limited multi-versioning and by allowing clients to independently resolve non-atomic reads. We demonstrate that, in contrast with existing algorithms, RAMP transactions incur limited overhead—even under high contention—and scale linearly to 100 servers.
National Science Foundation
Expeditions in Computing