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There is currently considerable enthusiasm around the MapReduce (MR) paradigm for large-scale data analysis [17]. Although the basic control flow of this framework has existed in parallel SQL database management systems (DBMS) for over 20 years, some have called MR a dramatically new computing model [8, 17]. In this paper, we describe and compare both(More)
Our previous work has shown that architectural and application shifts have resulted in modern OLTP databases increasingly falling short of optimal performance [10]. In particular , the availability of multiple-cores, the abundance of main memory, the lack of user stalls, and the dominant use of stored procedures are factors that portend a clean-slate(More)
The advent of affordable, shared-nothing computing systems portends a new class of parallel database management systems (DBMS) for on-line transaction processing (OLTP) applications that scale without sacrificing ACID guarantees [7, 9]. The performance of these DBMSs is predicated on the existence of an optimal database design that is tailored for the(More)
Benchmarking is an essential aspect of any database management system (DBMS) effort. Despite several recent advancements, such as pre-configured cloud database images and database-as-a-service (DBaaS) offerings, the deployment of a comprehensive testing platform with a diverse set of datasets and workloads is still far from being trivial. In many cases,(More)
The traditional wisdom for building disk-based relational database management systems (DBMS) is to organize data in heavily-encoded blocks stored on disk, with a main memory block cache. In order to improve performance given high disk latency, these systems use a multi-threaded architecture with dynamic record-level locking that allows multiple transactions(More)
First-generation streaming systems did not pay much attention to state management via ACID transactions (e.g., [3, 4]). S-Store is a data management system that combines OLTP transactions with stream processing. To create S-Store, we begin with H-Store, a main-memory transaction processing engine, and add primitives to support streaming. This includes(More)
Computer architectures are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented level of on-chip parallelism introduces a new dimension to scalability that current database management systems (DBMSs) were not designed for. In particular, as the number of cores increases, the problem(More)
A new emerging class of parallel database management systems (DBMS) is designed to take advantage of the partitionable work-loads of on-line transaction processing (OLTP) applications [23, 20]. Transactions in these systems are optimized to execute to completion on a single node in a shared-nothing cluster without needing to coordinate with other nodes or(More)
We present a framework for building and testing software in a heterogeneous, multiuser , distributed computing environment. Unlike other systems for automated builds and tests, our framework is not tied to a specific developer tool, revision control system, or testing framework, and allows access to computing resources across administrative boundaries.(More)