• Publications
  • Influence
The Design of the Borealis Stream Processing Engine
TLDR
Borealis is a second-generation distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Expand
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C-Store: A Column-oriented DBMS
TLDR
We present preliminary performance data on a subset of TPC-H and show that the system we are building, C-Store, is substantially faster than popular commercial products. Expand
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A comparison of approaches to large-scale data analysis
TLDR
We compare MapReduce (MR) and parallel database systems for large-scale data analysis. Expand
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HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads
TLDR
We explore the feasibility of building a hybrid system that takes the best features from both technologies; the prototype we built approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce-based systems. Expand
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H-store: a high-performance, distributed main memory transaction processing system
TLDR
We present H-Store, a distributed main memory OLTP database that operates on a distributed cluster of shared-nothing machines where the data resides entirely in main memory. Expand
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High-availability algorithms for distributed stream processing
TLDR
We study various recovery guarantees and pertinent recovery techniques that can meet the correctness and performance requirements of stream-processing applications. Expand
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Operator Scheduling in a Data Stream Manager
TLDR
This paper shows that having finer-grained control over processor allocation can make a significant difference to overall system performance by reducing various system overheads associated with continuous query execution. Expand
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Aurora: a data stream management system
TLDR
The Aurora system [1] is an experimental data stream management system with a fully functional prototype. Expand
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MapReduce and parallel DBMSs: friends or foes?
TLDR
MapReduce complements DBMSs since databases are not designed for extract-transform-load tasks, a MapReduce specialty. Expand
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Correlation Maps: A Compressed Access Method for Exploiting Soft Functional Dependencies
TLDR
We show that in a real application (SDSS) and widely used benchmark (TPC-H), there exist many cases of attribute correlation that can be exploited to accelerate queries. Expand
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