[1]
Thomson A, Diamond T, Weng S C, Ren K, Shao P, Abadi D J. Calvin: Fast distributed transactions for partitioned database systems. In Proc. the 2012 ACM SIGMOD International Conference on Management of Data, May 2012, pp.1-12.
[3]
Faleiro J M, Thomson A, Abadi D J. Lazy evaluation of transactions in database systems. In Proc. the 2014 ACM SIGMOD International Conference on Management of Data, June 2014, pp.15-26.
[7]
Tu S, Zheng W, Kohler E, Liskov B, Madden S. Speedy transactions in multicore in-memory databases. In Proc. the 24th ACM SIGOPS Symposium on Operating Systems Principles, November 2013, pp.18-32.
[9]
Arcangeli A, Cao M, McKenney P E, Sarma D. Using read-copy-update techniques for system V IPC in the Linux 2.5 kernel. In Proc. the 2003 USENIX Annual Technical Conference, June 2003, pp.297-309.
[10]
McKenney P E, Slingwine J D. Read-copy update: Using execution history to solve concurrency problems. In Proc. the 15th ISCA International Conference on Parallel and Distributed Computing and Systems, September 2002, pp.509-518.
[11]
Chen Y, Wei X, Shi J, Chen R, Chen H. Fast and general distributed transactions using RDMA and HTM. In Proc. the 11th European Conference on Computer Systems, April 2016, Article No. 26.
[12]
Stonebraker M, Madden S, Abadi D J, Harizopoulos S, Hachem N, Helland P. The end of an architectural era: (It’s time for a complete rewrite). In Proc. the 33rd International Conference on Very Large Data Bases, September 2007, pp.1150-1160.
[13]
Kimura H. FOEDUS: OLTP engine for a thousand cores and NVRAM. In Proc. the 2015 ACM SIGMOD International Conference on Management of Data, May 2015, pp.691-706.
[14]
Kalia A, Kaminsky M, Andersen D. G. FaSST: Fast, scalable and simple distributed transactions with two-sided (RDMA) datagram RPCs. In Proc. the 12th USENIX Symposium on Operating Systems Design and Implementation, November 2016, pp.185-201.
[15]
Wei X, Dong Z, Chen R, Chen H. Deconstructing RDMA-enabled distributed transactions: Hybrid is better! In Proc. the 13th USENIX Symposium on Operating Systems Design and Implementation, October 2018, pp.233-251.
[18]
Liskov B, Castro M, Shrira L, Adya A. Providing persistent objects in distributed systems. In Proc. the 13th European Conference on Object-Oriented Programming, June 1999, pp.230-257.
[21]
Yu X, Pavlo A, Sánchez D, Devadas S. TicToc: Time traveling optimistic concurrency control. In Proc. the 2016 ACM SIGMOD International Conference on Management of Data, June 2016, pp.1629-1642.
[22]
Weikum G, Vossen G. Transactional Information Systems: Theory, Algorithms, and the Practice of Concurrency Control and Recovery (1st edition). Morgan Kaufmann, 2001.
[24]
Bernstein P A, Hadzilacos V, Goodman N. Concurrency Control and Recovery in Database Systems (1st edition). Addison-Wesley, 1987.
[25]
Mohan C, Pirahesh H, Lorie R. Efficient and flexible methods for transient versioning of records to avoid locking by read-only transactions. In Proc. the 1992 ACM SIGMOD International Conference on Management of Data, June 1992, pp.124-133.
[27]
Diaconu C, Freedman C, Ismert E, Larson P Å, Mittal P, Stonecipher R, Verma N, Zwilling M. Hekaton: SQL server’s memory-optimized OLTP engine. In Proc. the 2013 ACM SIGMOD International Conference on Management of Data, June 2013, pp.1243-1254.
[28]
Levandoski J, Lomet D, Sengupta S, Stutsman R, Wang R. High performance transactions in deuteronomy. In Proc. the 7th Biennial Conference on Innovative Data Systems Research, January 2015, Article No. 44.
[29]
Neumann T, Mühlbauer T, Kemper A. Fast serializable multi-version concurrency control for main-memory database systems. In Proc. the 2015 ACM SIGMOD International Conference on Management of Data, May 2015, pp.677-689.
[31]
Li J, Michael E, Ports D R. Eris: Coordination-free consistent transactions using in-network concurrency control. In Proc. the 26th Symposium on Operating Systems Principles, October 2017, pp.104-120.
[32]
Wang Z, Qian H, Li J, Chen H. Using restricted transactional memory to build a scalable in-memory database. In Proc. the 9th European Conference on Computer Systems, April 2014, Article No. 26.
[33]
Wei X, Shi J, Chen Y, Chen R, Chen H. Fast in-memory transaction processing using RDMA and HTM. In Proc. the 25th Symposium on Operating Systems Principles, October 2015, pp.87-104.
[37]
Cowling J, Liskov B. Granola: Low-overhead distributed transaction coordination. In Proc. the 2012 USENIX Annual Technical Conference, June 2012, pp.223-235.
[41]
Zhang Y, Power R, Zhou S, Sovran Y, Aguilera M K, Li J. Transaction chains: Achieving serializability with low latency in geo-distributed storage systems. In Proc. the 24th ACM SIGOPS Symposium on Operating Systems Principles, November 2013, pp.276-291.
[42]
Mu S, Cui Y, Zhang Y, Lloyd W, Li J. Extracting more concurrency from distributed transactions. In Proc. the 11th USENIX Symposium on Operating Systems Design and Implementation, October 2014, pp.479-494.
[43]
Xie C, Su C, Littley C, Alvisi L, Kapritsos M, Wang Y. High-performance ACID via modular concurrency control. In Proc. the 25th Symposium on Operating Systems Principles, October 2015, pp.279-294.
[44]
Wang Z, Mu S, Cui Y, Yi H, Chen H, Li J. Scaling multicore databases via constrained parallel execution. In Proc. the 2016 ACM SIGMOD International Conference on Management of Data, June 2016, pp.1643-1658.