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Todays storage systems expose abstractions which are either too low-level (e.g., key-value store, raw-block store) that they require developers to re-invent the wheels, or too high-level (e.g., relational databases, Git) that they lack generality to support many classes of applications. In this work, we propose and implement a general distributed data storage system, called UStore, which has rich semantics. UStore delivers three key properties, namely immutability, sharing and security, which unify and add values to many classes of todays applications, and which also open the door for new applications. By keeping the core properties within the storage, UStore helps reduce application development efforts while offering high performance at hand. The storage embraces current hardware trends as key enablers. It is built around a data-structure similar to that of Git, a popular source code versioning system, but it also synthesizes many designs from distributed systems and databases. Our current implementation of UStore has better performance than general in-memory key-value storage systems, especially for version scan operations. We port and evaluate four applications on top of UStore: a Git-like application, a collaborative data science application, a transaction management application, and a blockchain application. We demonstrate that UStore enables faster development and the UStore-backed applications can have better performance than the existing implementations.
A benchmark study of modern distributed databases is an important source of information to select the right technology for managing data in the cloud-edge paradigms. To make the right decision, it is required to conduct an extensive experimental stud
Recently, the research on local repair codes is mainly confined to repair the failed nodes within each repair group. But if the extreme cases occur that the entire repair group has failed, the local code stored in the failed group need to be recovere
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In recent years, emerging hardware storage technologies have focused on divergent goals: better performance or lower cost-per-bit of storage. Correspondingly, data systems that employ these new technologies are optimized either to be fast (but expens
Redundant storage maintains the performance of distributed systems under various forms of uncertainty. This paper considers the uncertainty in node access and download service. We consider two access models under two download service models. In one a