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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., National Science Foundation (U.S.) (Grant 1065219), National Science Foundation (U.S.) (Grant 0704424)

Numerous sensitive databases are breached every year due to bugs in applications. These applications typically handle data for many users, and consequently, they have access to large amounts of confidential information. This paper describes IFDB, a DBMS that secures databases by using decentralized information flow control (DIFC). We present the Query by Label model, which introduces new abstractions for managing information flows in a relational database. IFDB also addresses several challenges inherent in bringing DIFC to databases, including how to handle transactions and integrity constraints without introducing covert channels. We implemented IFDB by modifying PostgreSQL, and extended two application environments, PHP and Python, to provide a DIFC platform. IFDB caught several security bugs and prevented information leaks in two web applications we ported to the platform. Our evaluation shows that IFDB's throughput is as good as PostgreSQL for a real web application, and about 1% lower for a database benchmark based on TPC-C.