Blockchain databases were designed to improve trust in centralized ecosystems, which dominate the market today, by introducing tamper-evidence features on top of a classical database. Compared to decentralized ledger technologies, blockchain databases are easier to use, and they can significantly reduce the operational and development costs. However, the existing blockchain databases do not equip multiple parties with tools to efficiently control common data written to the ledger. This paper describes Orion, a new open source blockchain database that introduces multi-sig and proof capabilities with extensive key-level access control, which enable parties to mutually control and validate a value written to the database. These unique capabilities, together with additional blockchain properties, provide users with features such as tamper-evidence, provenance, data lineage, authenticity, and non-repudiation, while using a standard data model and transactional APIs. We found our technology to be extremely useful in improving the integrity of a system and reducing mistakes, disputes, and fraud.

Transactional data structure libraries (TDSL) combine the ease-of-programming of transactions with the high performance and scalability of custom-tailored concurrent data structures. They can be very efficient thanks to their ability to exploit data structure semantics in order to reduce overhead, aborts, and wasted work compared to general-purpose software transactional memory. However, TDSLs were not previously used for complex use-cases involving long transactions and a variety of data structures. In this paper, we boost the performance and usability of a TDSL, towards allowing it to support complex applications. A key idea is nesting. Nested transactions create checkpoints within a longer transaction, so as to limit the scope of abort, without changing the semantics of the original transaction. We build a Java TDSL with built-in support for nested transactions over a number of data structures. We conduct a case study of a complex network intrusion detection system that invests a significant amount of work to process each packet. Our study shows that our library outperforms publicly available STMs twofold without nesting, and by up to 16x when nesting is used.

Transactional data structure libraries (TDSL) combine the ease-of-programming of transactions with the high performance and scalability of custom-tailored concurrent data structures. They can be very efficient thanks to their ability to exploit data structure semantics in order to reduce overhead, aborts, and wasted work compared to general-purpose software transactional memory. However, TDSLs were not previously used for complex use-cases involving long transactions and a variety of data structures.

Efficient ordered in-memory key-value (KV-)maps are paramount for the scalability of modern data platforms. In managed languages like Java, KV-maps face unique challenges due to the high overhead of garbage collection (GC).

Introduction. The execute-order-validate blockchain architecture, introduced by Hyperledger Fabric (HLF) [1], allows parallel transactions execution and validation, thus raising the need for transaction isolation. Today transaction isolation is attained by locking the entire state database (DB) during simulation of transactions and state update. This lock is one of the major bottlenecks as observed by previous work [3]. This work presents a new lock-free approach for providing transaction isolation.

One of the adverse effects of shrinking transistor sizes is that processors have become increasingly prone to hardware faults. At the same time, the number of cores per die rises. Consequently, core failures can no longer be ruled out, and future operating systems for many-core machines will have to incorporate fault tolerance mechanisms.