Speedy transactions in multicore in-memory databases

By Stephen Tu, Wenting Zheng, Eddie Kohler, Barbara H. Liskov, Samuel Madden. Symposium on Operating Systems Principles, 2013

647 citations recorded by the source corpus.

Silo is a new in-memory database that achieves excellent performance and scalability on modern multicore machines. Silo was designed from the ground up to use system memory and caches efficiently. For instance, it avoids all centralized contention points, including that of centralized transaction ID assignment. Silo's key contribution is a commit protocol based on optimistic concurrency control that provides serializability while avoiding all shared-memory writes for records that were only read. Though this might seem to complicate the enforcement of a serial order, correct logging and recovery is provided by linking periodically-updated epochs with the commit protocol. Silo provides the same guarantees as any serializable database without unnecessary scalability bottlenecks or much additional latency. Silo achieves almost 700,000 transactions per second on a standard TPC-C workload mix on a 32-core machine, as well as near-linear scalability. Considered per core, this is several times higher than previously reported results.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/780b40a506e7357c6857985ceec3498f6dd5051d

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In Computer Networks and Communications

Citations in the corpus

No compromises: distributed transactions with consistency, availability, and performance (2015, methodology): “We conservatively set the leases to 10ms in all our experiments and have not observed any false positives during their execution.”
In-Memory Big Data Management and Processing: A Survey (2015, methodology): “also well known research/open-source projects such as HStore [36], HyPer [35], Silo [39], Crescando [227], HYRISE”
Staring into the Abyss: An Evaluation of Concurrency Control with One Thousand Cores (2014, methodology): “This method was ﬁrst proposed in the Silo DBMS [42].”
Fast in-memory transaction processing using RDMA and HTM (2015, methodology): “In summary, the contributions of this paper are: • The ﬁrst design and implementation of exploiting the combination of HTM and RDMA to boost distributed transaction processing systems (§3).”