Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Aurora: a new model and architecture for data stream management
2003945 citationsDaniel J. Abadi, Don Carney et al.The VLDB Journalprofile →
Countries citing papers authored by Mitch Cherniack
Since
Specialization
Citations
This map shows the geographic impact of Mitch Cherniack's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mitch Cherniack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mitch Cherniack more than expected).
This network shows the impact of papers produced by Mitch Cherniack. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mitch Cherniack. The network helps show where Mitch Cherniack may publish in the future.
Co-authorship network of co-authors of Mitch Cherniack
This figure shows the co-authorship network connecting the top 25 collaborators of Mitch Cherniack.
A scholar is included among the top collaborators of Mitch Cherniack based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Mitch Cherniack. Mitch Cherniack is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Çetintemel, Uğur, et al.. (2013). Query Steering for Interactive Data Exploration.40 indexed citations
2.
Stonebraker, Michael, Ihab F. Ilyas, George Beskales, et al.. (2013). Data Curation at Scale: The Data Tamer System.111 indexed citations
Jain, Namit, Anand Srinivasan, Johannes Gehrke, et al.. (2008). Towards a streaming SQL standard. Proceedings of the VLDB Endowment. 1(2). 1379–1390.94 indexed citations
5.
Stonebraker, Michael, Chuck Bear, Uğur Çetintemel, et al.. (2007). One Size Fits All? Part 2: Benchmarking Studies.. Conference on Innovative Data Systems Research. 173–184.32 indexed citations
6.
Stonebraker, Michael, Chuck Bear, Mitch Cherniack, et al.. (2007). One Size Fits All? - Part 2: Benchmarking Results. 173–184.24 indexed citations
Balakrishnan, Hari, Magdalena Bałazińska, Don Carney, et al.. (2004). Retrospective on Aurora. The VLDB Journal. 13(4). 370–383.85 indexed citations
13.
Zdonik, Stanley B., Michael Stonebraker, Mitch Cherniack, et al.. (2003). The Aurora and Medusa Projects.. IEEE Data(base) Engineering Bulletin. 26. 3–10.88 indexed citations
14.
Cherniack, Mitch, Hari Balakrishnan, Magdalena Bałazińska, et al.. (2003). Scalable Distributed Stream Processing. Conference on Innovative Data Systems Research.310 indexed citations
Abadi, Daniel J., Don Carney, Uğur Çetintemel, et al.. (2003). Aurora. 666–666.126 indexed citations
17.
Cherniack, Mitch, Michael J. Franklin, & Stanley B. Zdonik. (2001). Data Management for Pervasive Computing. Very Large Data Bases. 727.20 indexed citations
18.
Cherniack, Mitch & Stan Zdonik. (1998). Changing the rules. 61–72.20 indexed citations
19.
Cherniack, Mitch & Stanley B. Zdonik. (1998). Inferring Function Semantics to Optimize Queries. 239–250.8 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.