Stan Zdonik
- Computer Networks and Communications top 0.2%
- Advanced Database Systems and Queries 41
- Distributed systems and fault tolerance 17
- Advanced Data Storage Technologies 7
- Peer-to-Peer Network Technologies 6
- Signal Processing top 0.2%
- Data Management and Algorithms 24
- Time Series Analysis and Forecasting 9
- Information Systems top 0.2%
- Cloud Computing and Resource Management 10
- Artificial Intelligence top 0.5%
- Data Stream Mining Techniques 4
Stan Zdonik
58 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Computer Networks and Communications 4.0k
- Signal Processing 1.9k
- Information Systems 1.8k
- Artificial Intelligence 1.6k
- Information Systems and Management 296
Countries citing papers authored by Stan Zdonik
This map shows the geographic impact of Stan Zdonik'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 Stan Zdonik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stan Zdonik more than expected).
Fields of papers citing papers by Stan Zdonik
This network shows the impact of papers produced by Stan Zdonik. 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 Stan Zdonik. The network helps show where Stan Zdonik may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stan Zdonik, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Cloud Observability: A MELTing Pot for Petabytes of Heterogenous Time Series. | 2021 | 1 |
| 2 | Encrypted Databases: From Theory to Systems. | 2021 | 3 |
| 3 | 2018 | 25 | |
| 4 | Data Ingestion for the Connected World. | 2017 | 34 |
| 5 | Handling Shared, Mutable State in Stream Processing with Correctness Guarantees. | 2015 | 8 |
| 6 | 2015 | 62 | |
| 7 | 2015 | 50 | |
| 8 | 2014 | 47 | |
| 9 | Proceedings of the 5th ACM international conference on Distributed event-based system | 2011 | 2 |
| 10 | Requirements for Science Data Bases and SciDB | 2009 | 110 |
| 11 | 2007 | 44 | |
| 12 | 2006 | 71 | |
| 13 | C-store: a column-oriented DBMSbreakdown → | 2005 | 591 |
| 14 | The Design of the Borealis Stream Processing Enginebreakdown → | 2005 | 784 |
| 15 | Scalable Distributed Stream Processing | 2003 | 310 |
| 16 | 1999 | 25 | |
| 17 | 1998 | 20 | |
| 18 | 1998 | 53 | |
| 19 | 1998 | 121 | |
| 20 | 1990 | 0 |
About Stan Zdonik
Stan Zdonik is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems, having authored 59 papers that have together received 4.8k indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (41 papers), Data Management and Algorithms (24 papers), Distributed systems and fault tolerance (17 papers), Cloud Computing and Resource Management (10 papers), Time Series Analysis and Forecasting (9 papers), Advanced Data Storage Technologies (7 papers), Peer-to-Peer Network Technologies (6 papers) and Data Stream Mining Techniques (4 papers). The work is most often cited by research in Computer Networks and Communications (4.0k citations), Signal Processing (1.9k citations) and Information Systems (1.8k citations). Stan Zdonik has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Michael Stonebraker, Mitch Cherniack, Uğur Çetintemel, Nesime Tatbul, Daniel J. Abadi, Don Carney, Ying Xing, Jeong-Hyon Hwang, Magdalena Bałazińska and Sang-Don Lee. Their work appears in journals such as ACM Computing Surveys, Proceedings of the VLDB Endowment and ACM SIGMOD Record.
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.