Scalable distributed transactions across heterogeneous stores

Typical cloud computing systems provide highly scalable and fault-tolerant data stores that may sacrifice other features like general multi-item transaction support. Recently techniques to implement multi-item transactions in these types of systems have focused on transactions across homogeneous data stores. Since applications access data in heterogeneous storage systems for legacy or interoperability reasons, we propose an approach that enables multi-item transactions with snapshot isolation across multiple heterogeneous data stores using only a minimal set of commonly implemented features such as single item consistency, conditional updates, and the ability to store additional meta-data. We define an client-coordinated transaction commitment protocol that does not rely on a central coordinating infrastructure. The application can take advantage of the scalability and fault-tolerance characteristics of modern key-value stores and access existing data in them, and also have multi-item transactional access guarantees with little performance impact. We have implemented our design in a Java library called Cherry Garcia (CG), that supports data store abstractions to Windows Azure Storage (WAS), Google Cloud Storage (GCS) and our own high-performance key-value store called Tora.