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As user privacy gains popularity and attention, and starts to shape relations between users and service providers, blockchain based solutions thrive for ways to relax immutability without sacrificing consistency. This work answers that need and presents the first design for a redactable execute-order-validate blockchain, that grants users with the right to be forgotten. The design is easy to adopt, as we exemplify by implementing it on top of Hyperledger Fabric. It modifies the block structure and extracts user data from the hash-chain without loosening any correctness or liveness criteria. We evaluate our design and show that it provides compliance with only a minimal performance overhead, making it a feasible add-on to any execute-ordervalidate blockchain system.

The arrival of persistent memory devices to consumer market has revived the interest in transactional durable algorithms. Persistent memory (PM) is touted as having two attributes that distinguish it from other storage technologies: byteaddressability and fast transactional persistence.In this work we investigate how these attributes differentiate PM from block storage in the context of buffered durability. We present a novel algorithm, TL4x, capable of providing buffered durable linearizable transactions with high scalability for disjoint writes and efficient persistence on either PM or block storage devices. TL4x is a softwareonly user-space solution that optimizes writes to persistent storage, providing buffered durable transactions whose cost is negligible compared to similar non-durable transactions. TL4x maintains a volatile consistent snapshot which is used for durability and shared with irrevocable read-only transactions, allowing long range-query operations to run in parallel with write transactions. We use TL4x to implement a transactional database engine that can outperform RocksDB by an order of magnitude.

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 generalpurpose 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, 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 nesting in 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 TL2 twofold without nesting, and by up to 16x when nesting is used. Finally, we discuss crosslibrary nesting, namely dynamic composition of transactions from multiple libraries.