Multi-Version Concurrency Control (MVCC) is a widely employed concurrency control mechanism, as it allows for execution modes where readers never block writers. However, most systems implement only snapshot isolation (SI) instead of full serializability. Adding serializability guarantees to existing SI implementations tends to be prohibitively expensive.We present a novel MVCC implementation for main-memory database systems that has very little overhead compared to serial execution with single-version concurrency control, even when maintaining serializability guarantees. Updating data in-place and storing versions as before-image deltas in undo buffers not only allows us to retain the high scan performance of single-version systems but also forms the basis of our cheap and fine-grained serializability validation mechanism. The novel idea is based on an adaptation of precision locking and verifies that the (extensional) writes of recently committed transactions do not intersect with the (intensional) read predicate space of a committing transaction. We experimentally show that our MVCC model allows very fast processing of transactions with point accesses as well as read-heavy transactions and that there is little need to prefer SI over full serializability any longer.

Abstract. Availability is an important security property for Internet services and a key ingredient of most service level agreements. It can be compromised by distributed Denial of Service (DoS) attacks. In this work we propose a formal pattern-based approach to study defense mechanisms against DoS attacks. We enhance pattern descriptions with formal models that allow the designer to give guarantees on the behavior of the proposed solution. The underlying executable specification formalism we use is the rewriting logic language Maude and its real-time and probabilistic extensions. We introduce the notion of stable availability, which means that with very high probability service quality remains very close to a threshold, regardless of how bad the DoS attack can get. Then we present two formal patterns which can serve as defenses against DoS attacks: the Adaptive Selective Verification (ASV) pattern, which enhances a communication protocol with a defense mechanism, and the Server Replicator (SR) pattern, which provisions additional resources on demand. However, ASV achieves availability without stability, and SR cannot achieve stable availability at a reasonable cost. As a main result we show, by statistical model checking with the PVeStA tool, that the composition of both patterns yields a new improved pattern which guarantees stable availability at a reasonable cost.

eScience and big data analytics applications are facing the challenge of efficiently evaluating complex queries over vast amounts of structured text data archived in network storage solutions. To analyze such data in traditional disk-based database systems, it needs to be bulk loaded, an operation whose performance largely depends on the wire speed of the data source and the speed of the data sink, i.e., the disk. As the speed of network adapters and disks has stagnated in the past, loading has become a major bottleneck. The delays it is causing are now ubiquitous as text formats are a preferred storage format for reasons of portability.But the game has changed: Ever increasing main memory capacities have fostered the development of in-memory database systems and very fast network infrastructures are on the verge of becoming economical. While hardware limitations for fast loading have disappeared, current approaches for main memory databases fail to saturate the now available wire speeds of tens of Gbit/s. With Instant Loading, we contribute a novel CSV loading approach that allows scalable bulk loading at wire speed. This is achieved by optimizing all phases of loading for modern super-scalar multi-core CPUs. Large main memory capacities and Instant Loading thereby facilitate a very efficient data staging processing model consisting of instantaneous load -work-unload cycles across data archives on a single node. Once data is loaded, updates and queries are efficiently processed with the flexibility, security, and high performance of relational main memory databases.