Advanced Databases Reading List » »

2024 »

OVERVIEW PAPERS (AS2)
• O1 - [DB/LLMS]
  From Large Language Models to Databases and Back: A Discussion on Research and Education. Sihem Amer-Yahia, Angela Bonifati, Lei Chen, Guoliang Li, Kyuseok Shim, Jianliang Xu, and Xiaochun Yang. 2023.  SIGMOD Rec. 52, 3 (September 2023), 49–56.
• O2 - [DB/Hardware]
  Data Processing with FPGAs on Modern Architectures.
Wenqi Jiang, Dario Korolija, and Gustavo Alonso. 2023. In Companion of the 2023 International Conference on Management of Data (SIGMOD '23). Association for Computing Machinery, New York, NY, USA, 77–82.
• O3 - [DB/Forensics]
  Where do Databases and Digital Forensics meet? A Comprehensive Survey and Taxonomy.  Danilo B. Seufitelli, Michele A. Brandão, Ayane C. A. Fernandes, Kayque M. Siqueira, and Mirella M. Moro. 2023.  SIGMOD Rec. 52, 3 (September 2023), 18–29.
• O6 - [DB/Privacy]
  Private Information Retrieval in Large Scale Public Data Repositories. Ishtiyaque Ahmad, Divyakant Agrawal, Amr El Abbadi, and Trinabh Gupta. 2023.  Proc. VLDB Endow. 16, 12 (August 2023), 3868–3871.
• O7 - [DB/Networks]
  Databases on Modern Networks: A Decade of Research That Now Comes into Practice. Alberto Lerner, Carsten Binnig, Philippe Cudré-Mauroux, Rana Hussein, Matthias Jasny, Theo Jepsen, Dan R. K. Ports, Lasse Thostrup, and Tobias Ziegler. 2023. Proc. VLDB Endow. 16, 12 (August 2023), 3894–3897.
• O8 - [DB/Clouds]
  Cloud databases: new techniques, challenges, and opportunities Guoliang Li, Haowen Dong, and Chao Zhang. 2022.  Proc. VLDB Endow. 15, 12 (August 2022), 3758–3761.

TECHNICAL PAPERS (AS3)
• R1 - [Hardware]
  Data Pipes: Declarative Control over Data Movement. Lukas Vogel (Technische Universität München); Daniel Ritter (SAP); Danica Porobic (Oracle); Pinar Tozun (IT University of Copenhagen)*; Tianzheng Wang (Simon Fraser University); Alberto Lerner (University of Friborug), Conference on Innovative Data Systems Research (CIDR), 2023.
• R2 - [Hardware]
  DASH: Asynchronous Hardware Data Processing Services. Norman May (SAP SE)*; Daniel Ritter (SAP); Andre Dossinger (SAP SE); Christian Faerber (Intel Corporation); Suleyman Demirsoy (Intel Corp.), Conference on Innovative Data Systems Research (CIDR), 2023.
• R5 - [GeoDBs]
  Chablis: Fast and General Transactions in Geo-Distributed Systems. Tamer Eldeeb (Columbia University)*; Philip Bernstein (Microsoft Research); Asaf Cidon (Columbia University); Junfeng Yang (Columbia University), Conference on Innovative Data Systems Research (CIDR), 2024.
• R7 - [Edge]
  The Tipping Point of Edge-Cloud Data Management. Faisal Nawab (University of California at Irvine)*; Moshe Shadmon (AnyLog), Conference on Innovative Data Systems Research (CIDR), 2024.
• R9 - [Cloud]
  Off-the-shelf Data Analytics on Serverless. Michal Wawrzoniak (ETHZ)*; Gianluca Moro (ETH Zurich); Rodrigo Bruno (Instituto Superior Técnico / INESC-ID Lisboa); Ana Klimovic (ETH Zurich); Gustavo Alonso (ETHZ), Conference on Innovative Data Systems Research (CIDR), 2024.
• R11 - [GenAI]
  Turning Databases Into Generative AI Machines. Alekh Jindal (SmartApps)*; Shi Qiao (SmartApps Inc); Sathwik Madhula (SmartApps); Kanupriya Raheja (SmartApps); Sandhya Jain (SmartApps), Conference on Innovative Data Systems Research (CIDR), 2024.
• R13 - [GenAI]
  VerifAI: Verified Generative AI. Nan Tang (HKUST, GZ); Chenyu Yang (HKUST, GZ); Ju Fan (Renmin University of China)*; Lei Cao (University of Arizona/MIT); Yuyu Luo (HKUST, GZ); Alon Y Halevy (Facebook), Conference on Innovative Data Systems Research (CIDR), 2024.

2023 »

OVERVIEW PAPERS (AS2)
• O1 - [Cloud Databases]
  Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities. Vivek Narasayya and Surajit Chaudhuri. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2465–2473. https://doi.org/10.1145/3514221.3522566
• O2 - [HTAP Databases]
  HTAP Databases: What is New and What is Next. Guoliang Li and Chao Zhang. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2483–2488. https://doi.org/10.1145/3514221.3522565
• O3 - [Spatial Data / IoT]
  Spatial Data Quality in the IoT Era: Management and Exploitation. Huan Li, Bo Tang, Hua Lu, Muhammad Aamir Cheema, and Christian S. Jensen. 2022. . In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2474–2482. https://doi.org/10.1145/3514221.3522568
• O4 - [Data Integration]
  Responsible Data Integration: Next-generation Challenges. Fatemeh Nargesian, Abolfazl Asudeh, and H. V. Jagadish. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2458–2464. https://doi.org/10.1145/3514221.3522567
• O5 - [KV Stores]
  Key-Value Storage Engines. Stratos Idreos and Mark Callaghan. 2020. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data (SIGMOD '20). Association for Computing Machinery, New York, NY, USA, 2667–2672. https://doi.org/10.1145/3318464.3383133
• O6 - [Blockchain Databases]
  Database and Distributed Computing Foundations of Blockchains. Sujaya Maiyya, Victor Zakhary, Mohammad Javad Amiri, Divyakant Agrawal, and Amr El Abbadi. 2019. In Proceedings of the 2019 International Conference on Management of Data (SIGMOD '19). Association for Computing Machinery, New York, NY, USA, 2036–2041. https://doi.org/10.1145/3299869.3314030
• O8 - [Buffer Pools / MMAP]
  Are You Sure You Want to Use MMAP in Your Database Management System? Crotty, Andrew and Leis, Viktor and Pavlo, Andrew. 2022. In 10th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Chaminade, CA, USA, January 9-12, 2022.

TECHNICAL PAPERS (AS3)
• R1 - [Blockchain]
  LedgerView: Access-Control Views on Hyperledger Fabric. Pingcheng Ruan, Yaron Kanza, Beng Chin Ooi, and Divesh Srivastava. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2218–2231. https://doi.org/10.1145/3514221.3526046
• R2 - [Optimization / Microsoft]
  Deploying a Steered Query Optimizer in Production at Microsoft. Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, and Alekh Jindal 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2299–2311. https://doi.org/10.1145/3514221.3526052
• R3 - [Queries / Encrypted Data]
  Efficient confidentiality-preserving data analytics over symmetrically encrypted datasets., Savvas Savvides, Darshika Khandelwal, and Patrick Eugster. 2020. Proc. VLDB Endow. 13, 8 (April 2020), 1290–1303. https://doi.org/10.14778/3389133.3389144
• R4 - [Data Lakehouses / Databricks]
  Photon: A Fast Query Engine for Lakehouse Systems,, Alexander Behm, Shoumik Palkar, Utkarsh Agarwal, Timothy Armstrong, David Cashman, Ankur Dave, Todd Greenstein, Shant Hovsepian, Ryan Johnson, Arvind Sai Krishnan, Paul Leventis, Ala Luszczak, Prashanth Menon, Mostafa Mokhtar, Gene Pang, Sameer Paranjpye, Greg Rahn, Bart Samwel, Tom van Bussel, Herman van Hovell, Maryann Xue, Reynold Xin, and Matei Zaharia. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2326–2339. https://doi.org/10.1145/3514221.3526054
• R6 - [Distributed Multi-tenant / Alibaba]
  ESDB: Processing Extremely Skewed Workloads in Real-time. Jiachi Zhang, Shi Cheng, Zhihui Xue, Jianjun Deng, Cuiyun Fu, Wenchao Zhou, Sheng Wang, Changcheng Chen, and Feifei Li. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2286–2298. https://doi.org/10.1145/3514221.3526051
• R7 - [GPU Joins]
  Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects. Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, and Volker Markl. 2022. . In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 1017–1032. https://doi.org/10.1145/3514221.3517911
• R8 - [Streaming / RDMA]
  KafkaDirect: Zero-copy Data Access for Apache Kafka over RDMA Networks Konstantin Taranov, Steve Byan, Virendra Marathe, and Torsten Hoefler. 2022. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22). Association for Computing Machinery, New York, NY, USA, 2191–2204. https://doi.org/10.1145/3514221.3526056

2020 »

OVERVIEW PAPERS (AS1)
• O1 [IoT]
  The NebulaStream Platform for Data and Application Management in the Internet of Things., Steffen Zeuch (DFKI GmbH)*; Ankit Chaudhary (TU Berlin); Bonaventura Del Monte (Technische Universität Berlin); Haralampos Gavriilidis (TU Berlin); Dimitrios Giouroukis (TU Berlin); Philipp Marian Grulich (Technische Universität Berlin); Sebastian Bress (TU Berlin); Jonas Traub (Technische Universität Berlin); Volker Markl (Technische Universität Berlin), 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.
• O2 [Machine Learning]
  Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML, Ashvin Agrawal (Microsoft);Rony Chatterjee (Microsoft); Carlo Curino (Microsoft)*; Avrilia Floratou (Microsoft); Neha Godwal (Microsoft); Matteo Interlandi (Microsoft); Alekh Jindal (Microsoft); Konstantinos Karanasos (Microsoft); Subru Krishnan (Microsoft); Brian Kroth (Microsoft); Jyoti Leeka (Microsoft Research); Kwanghyun Park (Microsoft Gray Systems Lab); Hiren Patel (Microsoft); Olga Poppe (Microsoft); Fotis Psallidas (Microsoft); Raghu Ramakrishnan (Microsoft); Abhishek Roy (Microsoft); Karla Saur (Microsoft); Rathijit Sen (Microsoft); Markus Weimer (Microsoft); Travis Wright (Microsoft); Yiwen Zhu (Microsoft) 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.
• O3 [Relational]
  Compiling PL/SQL Away, Christian Duta (Universität Tübingen), Denis Hirn (Universität Tübingen), Torsten Grust (Universität Tübingen) 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.
• O4 [Blockchain]
  AnyLog: a Grand Unification of the Internet of Things, Faisal Nawab (UC Santa Cruz)*; Daniel J Abadi (UMD); Owen Arden (UC Santa Cruz); Moshe Shadmon (AnyLog) 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.
• O5 [VisualDB]
  VisualWorldDB: A DBMS for the Visual World, Brandon Haynes (University of Washington)*; Maureen Daum (University of Washington); Amrita Mazumdar (University of Washington); Magdalena Balazinska (UW); Alvin Cheung (University of California, Berkeley); Luis Ceze (University of Washington) 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.
• O6 [Workflows]
  Your notebook is not crumby enough, REPLace it, Mike Brachmann (Buffalo); William Spoth (University at Buffalo); Oliver A Kennedy (University at Buffalo, SUNY)*; Boris Glavic (Illinois Institute of Technology); Heiko Mueller (NYU); Sonia Castelo Quispe (New York University); Carlos Bautista (NYU); JulianaFreire(New York University) 9th Biennial Conference on Innovative Data Systems Research (CIDR ‘19), Asilomar, California, USA, January 13-16, 2019.

TECHNICAL PAPERS (AS3)
• R1 [Spatial]
  MapReuse: Recycling Routing API Queries, R. Stanojevic, S. Abbar and M. Mokbel, 2019 20th IEEE International Conference on Mobile Data Management (MDM), Hong Kong, Hong Kong, 2019, pp. 279-287, doi: 10.1109/MDM.2019.00-47
• R2 [ML]
  Data Platform for Machine Learning, R. Pulkit Agrawal, Rajat Arya, Aanchal Bindal, Sandeep Bhatia, Anupriya Gagneja, Joseph Godlewski, Yucheng Low, Timothy Muss, Mudit Manu Paliwal, Sethu Raman, Vishrut Shah, Bochao Shen, Laura Sugden, Kaiyu Zhao, and Ming-Chuan Wu. 2019. In Proceedings of the 2019 International Conference on Management of Data (SIGMOD ’19). Association for Computing Machinery, New York, NY, USA, 1803–1816. DOI: https://doi.org/10.1145/3299869.3314050
• R3 [Cloud DBs]
  Socrates: The New SQL Server in the Cloud", Panagiotis Antonopoulos, Alex Budovski, Cristian Diaconu, Alejandro Hernandez Saenz, Jack Hu, Hanuma Kodavalla, Donald Kossmann, Sandeep Lingam, Umar Farooq Minhas, Naveen Prakash, Vijendra Purohit, Hugh Qu, Chaitanya Sreenivas Ravella, Krystyna Reisteter, Sheetal Shrotri, Dixin Tang, and Vikram Wakade. 2019. In Proceedings of the 2019 International Conference on Management of Data (SIGMOD ’19). Association for Computing Machinery, New York, NY, USA, 1743–1756. DOI: https://doi.org/10.1145/3299869.3314047
• R4 [Blockchain DBs]
  CAPER: a cross-application permissioned blockchain, Mohammad Javad Amiri, Divyakant Agrawal, and Amr El Abbadi. 2019. . Proc. VLDB Endow. 12, 11 (July 2019), 1385–1398. DOI: https://doi.org/10.14778/3342263.3342275
• R5 [Mobile DBs]
  DASH: database shadowing for mobile DBMS, Youjip Won, Sundoo Kim, Juseong Yun, Dam Quang Tuan, and Jiwon Seo. 2019. Proc. VLDB Endow. 12, 7 (March 2019), 793–806. DOI:https://doi.org/10.14778/3317315.3317321
• R6 [Cloud DBs]
  Hillview: a trillion-cell spreadsheet for big data, Mihai Budiu, Parik** Gopalan, Lalith Suresh, Udi Wieder, Han Kruiger, and Marcos K. Aguilera. 2019. Proc. VLDB Endow. 12, 11 (July 2019), 1442–1457. DOI: https://doi.org/10.14778/3342263.3342279.

2019 »

OVERVIEW PAPERS (AS1)
• O1 [Machine Learning]
  Data Lifecycle Challenges in Production Machine Learning: A Survey, Neoklis Polyzotis, Sudip Roy, Steven Euijong Whang, and Martin Zinkevich. 2018, SIGMOD Rec. 47, 2 (December 2018), 17-28. DOI: https://doi.org/10.1145/3299887.3299891.
• O2 [Stream Processing]
  Stream Processing Languages in the Big Data Era. Martin Hirzel, Guillaume Baudart, Angela Bonifati, Emanuele Della Valle, Sherif Sakr, and Akrivi Akrivi Vlachou. 2018, SIGMOD Rec. 47, 2 (December 2018), 29-40. DOI: https://doi.org/10.1145/3299887.3299892.
• O3 [Temporal Data]
  Looking Back to Look Forward. Xin Luna Dong, Anastasios Kementsietsidis, and Wang-Chiew Tan. 2016. A Time Machine for Information: SIGMOD Rec. 45, 2 (September 2016), 23-32. DOI: http://dx.doi.org/10.1145/3003665.3003671
• O4 [Data Integration]
  The Data Civilizer System, Dong Deng, Raul Castro Fernandez, Ziawasch Abedjan, Sibo Wang, Michael Stonebraker, Ahmed K. Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Nan Tang, CIDR 2017, 8th Biennial Conference on Innovative Data Systems Research, Chaminade, CA, USA, January 8-11, 2017.
• O5 [Self-Driving DBs]
  Self-Driving Database Management Systems, Andrew Pavlo, Gustavo Angulo, Joy Arulraj, Haibin Lin, Jiexi Lin, Lin Ma, Prashanth Menon, Todd C. Mowry, Matthew Perron, Ian Quah, Siddharth Santurkar, Anthony Tomasic, Skye Toor, Dana Van Aken, Ziqi Wang, Yingjun Wu, Ran Xian, Tieying Zhang: CIDR 2017, 8th Biennial Conference on Innovative Data Systems Research, Chaminade, CA, USA, January 8-11, 2017.
• O6 [DNA DBMS]
  OligoArchive: Using DNA in the DBMS storage hierarchy, Appuswamy, Raja; Lebrigand, Kevin; Barbry, Pascal; Antonini, Marc; Madderson, Olivier; Freemont, Paul; McDonald, James; Heinis, Thomas, CIDR 2019, Biennal Conference on Innovative Data Systems Research, January 13-16, 2019, Asilomar, California, USA.
• O7 [DB Amnesia]
  A Database System with Amnesia, Martin L. Kersten, Lefteris Sidirourgos, CIDR 2017, 8th Biennial Conference on Innovative Data Systems Research, Chaminade, CA, USA, January 8-11, 2017.
• O8 [SQL 2016]
  The New and Improved SQL: 2016 Standard, Jan Michels, Keith Hare, Krishna Kulkarni, Calisto Zuzarte, Zhen Hua Liu, Beda Hammerschmidt, and Fred Zemke. 2018. SIGMOD Rec. 47, 2 (December 2018), 51-60. DOI: https://doi.org/10.1145/3299887.3299897

TECHNICAL PAPERS (AS3)
• R1 [Blockchains]
  vChain: Enabling Verifiable Boolean Range Queries over Blockchain Databases. C. Xu, C. Zhang, and J. Xu. Proc. the ACM SIGMOD International Conference on Management of Data (SIGMOD '19), Amsterdam, Netherlands, 2019.
• R2 [Knowledge Bases]
  Query-Driven On-The-Fly Knowledge Base Construction., Dat Ba Nguyen, Abdalghani Abujabal, Khanh Tran, Martin Theobald, Gerhard Weikum: 66-79, Volume 11, Number 1, September 2017, PVLDB 2017.
• R3 [Virtual Reality and DBs] LightDB: A DBMS for Virtual Reality. Brandon Haynes, Amrita Mazumdar, Armin Alaghi, Magdalena Balazinska, Luis Ceze, and Alvin Cheung, PVLDB 2018.
• R4 [SQLite]
  SQL statement logging for making SQLite truly lite, Jong-Hyeok Park, Gihwan Oh, and Sang-Won Lee. 2017. Proc. VLDB Endow. 11, 4 (December 2017), 513-525. DOI: https://doi.org/10.1145/3186728.3164146.
• R5 [In Memory]
  Adaptive Energy-Control for In-Memory Database Systems, Thomas Kissinger, Dirk Habich, and Wolfgang Lehner. 2018. . In Proceedings of the 2018 International Conference on Management of Data (SIGMOD '18). ACM, New York, NY, USA, 351-364. DOI: https://doi.org/10.1145/3183713.3183756.
• R6 [Spatial]
  Efficient Selection of Geospatial Data on Maps for Interactive and Visualized Exploration. Tao Guo, Kaiyu Feng, Gao Cong, and Zhifeng Bao. 2018. In Proceedings of the 2018 International Conference on Management of Data (SIGMOD '18). ACM, New York, NY, USA, 567-582. DOI: https://doi.org/10.1145/3183713.3183738.
• R7 [OracleJoins]
  Accelerating Joins and Aggregations on the Oracle In-Memory Database, S. Chavan, A. Hopeman, S. Lee, D. Lui, A. Mylavarapu and E. Soylemez, 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, 2018, pp. 1441-1452. doi: 10.1109/ICDE.2018.00163.
• R8 [CloudkitApple]
  Cloudkit: structured storage for mobile applications., Alexander Shraer, Alexandre Aybes, Bryan Davis, Christos Chrysafis, Dave Browning, Eric Krugler, Eric Stone, Harrison Chandler, Jacob Farkas, John Quinn, Jonathan Ruben, Michael Ford, Mike McMahon, Nathan Williams, Nicolas Favre-Felix, Nihar Sharma, Ori Herrnstadt, Paul Seligman, Raghav Pisolkar, Scott Dugas, Scott Gray, Shirley Lu, Sytze Harkema, Valentin Kravtsov, Vanessa Hong, Yizuo Tian, and Wan Ling Yih. 2018. Proc. VLDB Endow. 11, 5 (January 2018), 540-552. DOI: https://doi.org/10.1145/3187009.3164138.

2017 »

OVERVIEW PAPERS (AS1)
• [O1] (Knowledge Bases / Yago)
  Database and information-retrieval methods for knowledge discovery, Gerhard Weikum, Gjergji Kasneci, Maya Ramanath, and Fabian Suchanek. 2009. Commun. ACM 52, 4 (April 2009), 56-64. DOI: https://doi.org/10.1145/1498765.1498784.
• [O2] (Knowledge Bases / Deepdive)
  DeepDive: declarative knowledge base construction, Ce Zhang, Christopher Ré, Michael Cafarella, Christopher De Sa, Alex Ratner, Jaeho Shin, Feiran Wang, and Sen Wu. 2017. Commun. ACM 60, 5 (April 2017), 93-102. DOI: https://doi.org/10.1145/3060586.
• [O3] (NoDB)
  NoDB: efficient query execution on raw data files.Ioannis Alagiannis, Renata Borovica-Gajic, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. 2015. Commun. ACM 58, 12 (November 2015), 112-121. DOI: https://doi.org/10.1145/2830508.
• [O4] (Data Stores)
  10 rules for scalable performance in 'simple operation' datastores, Michael Stonebraker and Rick Cattell. 2011. Commun. ACM 54, 6 (June 2011), 72-80. DOI: https://doi.org/10.1145/1953122.1953144.
• [O5] (Blockchain DBs)
  Not ACID, not BASE, but SALT - A Transaction Processing Perspective on Blockchains, Tai S., Eberhardt J. and Klems M. (2017).In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 755-764. DOI: 10.5220/0006408207550764.
• [O6] (Autonomous DBs / Peloton)
  Self-Driving Database Management Systems, A. Pavlo, G. Angulo, J. Arulraj, H. Lin, J. Lin, L. Ma, P. Menon, T. Mowry, M. Perron, I. Quah, S. Santurkar, A. Tomasic, S. Toor, D. V. Aken, Z. Wang, Y. Wu, R. Xian, and T. Zhang, in CIDR 2017, Conference on Innovative Data Systems Research, 2017.
• [O7] (Data Science)
  Data science: challenges and directions. Commun. ACM 60, 8 (July 2017), 59-68. DOI: https://doi.org/10.1145/3015456.

TECHNICAL PAPERS (AS3)
• [R1] (DNA Storage)
  A DNA-Based Archival Storage System, James Bornholt, Randolph Lopez, Douglas M. Carmean, Luis Ceze, Georg Seelig, and Karin Strauss. 2016. A DNA-Based Archival Storage System. In Proceedings of the Twenty-First International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '16). ACM, New York, NY, USA, 637-649. DOI: https://doi.org/10.1145/2872362.2872397
• [R2] (In Memory / Hekaton)
  Hekaton: SQL server's memory-optimized OLTP engine. Cristian Diaconu, Craig Freedman, Erik Ismert, Per-Ake Larson, Pravin Mittal, Ryan Stonecipher, Nitin Verma, and Mike Zwilling. 2013. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (SIGMOD '13). ACM, New York, NY, USA, 1243-1254. DOI: http://dx.doi.org/10.1145/2463676.2463710
• [R3] (Big Spatial Data / TrafficDB)
  TrafficDB: HERE's high performance shared-memory data store, Ricardo Fernandes, Piotr Zaczkowski, Bernd Göttler, Conor Ettinoffe, and Anis Moussa. 2016. Proc. VLDB Endow. 9, 13 (September 2016), 1365-1376. DOI: http://dx.doi.org/10.14778/3007263.3007274
• [R4] (NVRAM)
  Let's Talk About Storage   Recovery Methods for Non-Volatile Memory Database Systems., Joy Arulraj, Andrew Pavlo, and Subramanya R. Dulloor. 2015. Let's Talk About Storage   Recovery Methods for Non-Volatile Memory Database Systems. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD '15). ACM, New York, NY, USA, 707-722. DOI: https://doi.org/10.1145/2723372.2749441
• [R5] (Query Optimization)
  The MemSQL Query Optimizer: A modern optimizer for real-time analytics in a distributed database., Jack Chen, Samir Jindel, Robert Walzer, Rajkumar Sen, Nika Jimsheleishvilli, and Michael Andrews. 2016. Proc. VLDB Endow. 9, 13 (September 2016), 1401-1412. DOI: http://dx.doi.org/10.14778/3007263.3007277
• [R6] (Telco Big Data)
  City-Scale Localization with Telco Big Data. Fangzhou Zhu, Chen Luo, Mingxuan Yuan, Yijian Zhu, Zhengqing Zhang, Tao Gu, Ke Deng, Weixiong Rao, and Jia Zeng. 2016. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM '16). ACM, New York, NY, USA, 439-448. DOI: https://doi.org/10.1145/2983323.2983345
• [R7] (Joins)
  THERMAL-JOIN: A Scalable Spatial Join for Dynamic Workloads. Farhan Tauheed, Thomas Heinis, and Anastasia Ailamaki. 2015. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD '15). ACM, New York, NY, USA, 939-950. DOI: https://doi.org/10.1145/2723372.2749434

2016 »

No course offering

2015 »

• [R1] (SQLite/Flash)
  X-FTL: transactional FTL for SQLite databases. Woon-Hak Kang, Sang-Won Lee, Bongki Moon, Gi-Hwan Oh, and Changwoo Min. 2013. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (SIGMOD '13). ACM, New York, NY, USA, 97-108. DOI=10.1145/2463676.2465326 http://doi.acm.org/10.1145/2463676.2465326
• [R2] (Flink)
  The Stratosphere platform for big data analytics. Alexander Alexandrov, Rico Bergmann, Stephan Ewen, Johann-Christoph Freytag, Fabian Hueske, Arvid Heise, Odej Kao, Marcus Leich, Ulf Leser, Volker Markl, Felix Naumann, Mathias Peters, Astrid Rheinländer, Matthias J. Sax, Sebastian Schelter, Mareike Höger, Kostas Tzoumas, and Daniel Warneke. 2014. The VLDB Journal 23, 6 (December 2014), 939-964. DOI=10.1007/s00778-014-0357-y
• [R3] (Mobile/IoT)
  A performance study of big data on small nodes. Dumitrel Loghin, Bogdan Marius Tudor, Hao Zhang, Beng Chin Ooi, and Yong Meng Teo. 2015. Proc. VLDB Endow. 8, 7 (February 2015), 762-773. DOI=10.14778/2752939.2752945
• [R4] (NewSQL)
  Calvin: fast distributed transactions for partitioned database systems., Alexander Thomson, Thaddeus Diamond, Shu-Chun Weng, Kun Ren, Philip Shao, and Daniel J. Abadi. 2012. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD '12). ACM, New York, NY, USA, 1-12. DOI=10.1145/2213836.2213838
• [R5] (Big Data Stores)
  On brewing fresh espresso: LinkedIn's distributed data serving platform. Lin Qiao, Kapil Surlaker, Shirshanka Das, Tom Quiggle, Bob Schulman, Bhaskar Ghosh, Antony Curtis, Oliver Seeliger, Zhen Zhang, Aditya Auradar, Chris Beaver, Gregory Brandt, Mihir Gandhi, Kishore Gopalakrishna, Wai Ip, Swaroop Jgadish, Shi Lu, Alexander Pachev, Aditya Ramesh, Abraham Sebastian, Rupa Shanbhag, Subbu Subramaniam, Yun Sun, Sajid Topiwala, Cuong Tran, Jemiah Westerman, and David Zhang. 2013. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (SIGMOD '13). ACM, New York, NY, USA, 1135-1146. DOI=10.1145/2463676.2465298
• [R6] (Big Streams)
  MillWheel: fault-tolerant stream processing at internet scale. Tyler Akidau, Alex Balikov, Kaya Bekiroğlu, Slava Chernyak, Josh Haberman, Reuven Lax, Sam McVeety, Daniel Mills, Paul Nordstrom, and Sam Whittle. 2013. Proc. VLDB Endow. 6, 11 (August 2013), 1033-1044. DOI=10.14778/2536222.2536229
• [R7] (Big Spatial)
  AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data. Ahmed M. Aly, Ahmed R. Mahmood, Mohamed S. Hassan, Walid G. Aref, Mourad Ouzzani, Hazem Elmeleegy, Thamir Qadah. VLDB 2016.
• [R8] (Big Data Warehouses)
  Dremel: interactive analysis of web-scale datasets. Sergey Melnik, Andrey Gubarev, Jing Jing Long, Geoffrey Romer, Shiva Shivakumar, Matt Tolton, and Theo Vassilakis. 2011. Commun. ACM 54, 6 (June 2011), 114-123. DOI=10.1145/1953122.1953148
• [R9] (Analytics)
  Telco Churn Prediction with Big Data. Yiqing Huang, Fangzhou Zhu, Mingxuan Yuan, Ke Deng, Yanhua Li, Bing Ni, Wenyuan Dai, Qiang Yang, and Jia Zeng. 2015. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD '15). ACM, New York, NY, USA, 607-618. DOI=10.1145/2723372.2742794

2014 »

• [R1] (NoDBs)
  NoDB: efficient query execution on raw data files, Ioannis Alagiannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. 2012. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD '12). ACM, New York, NY, USA, 241-252. DOI=10.1145/2213836.2213864
• [R2] (Logging)
  Aether: a scalable approach to logging, Ryan Johnson, Ippokratis Pandis, Radu Stoica, Manos Athanassoulis, and Anastasia Ailamaki. 2010. Proc. VLDB Endow. 3, 1-2 (September 2010), 681-692. DOI=10.14778/1920841.1920928
• [R3] (Graph Databases)
  TAO: Facebook's distributed data store for the social graph., Nathan Bronson, Zach Amsden, George Cabrera, Prasad Chakka, Peter Dimov, Hui Ding, Jack Ferris, Anthony Giardullo, Sachin Kulkarni, Harry Li, Mark Marchukov, Dmitri Petrov, Lovro Puzar, Yee Jiun Song, and Venkat Venkataramani. 2013. In Proceedings of the 2013 USENIX conference on Annual Technical Conference (USENIX ATC'13). USENIX Association, Berkeley, CA, USA, 49-60.
• [R4] (Real-Time Analysis)
  Earlybird: Real-Time Search at Twitter, Michael Busch, Krishna Gade, Brian Larson, Patrick Lok, Samuel Luckenbill, and Jimmy Lin. 2012. . In Proceedings of the 2012 IEEE 28th International Conference on Data Engineering (ICDE'12). IEEE Computer Society, Washington, DC, USA, 1360-1369. DOI=10.1109/ICDE.2012.149
• [R5] (Main-Memory Processing)
  Storm@twitter, Ankit Toshniwal, Siddarth Taneja, Amit Shukla, Karthik Ramasamy, Jignesh M. Patel, Sanjeev Kulkarni, Jason Jackson, Krishna Gade, Maosong Fu, Jake Donham, Nikunj Bhagat, Sailesh Mittal, and Dmitriy Ryaboy. 2014. . In Proceedings of the 2014 ACM SIGMOD international conference on Management of data (SIGMOD '14). ACM, New York, NY, USA, 147-156. DOI=10.1145/2588555.2595641
• [R6] (Crowdsourcing)
  Human-powered sorts and joins, Adam Marcus, Eugene Wu, David Karger, Samuel Madden, and Robert Miller. 2011. Proc. VLDB Endow. 5, 1 (September 2011), 13-24. DOI=10.14778/2047485.2047487
• [R7] (JSON)
  JSON data management: supporting schema-less development in RDBMS, Zhen Hua Liu, Beda Hammerschmidt, and Doug McMahon. 2014. . In Proceedings of the 2014 ACM SIGMOD international conference on Management of data (SIGMOD '14). ACM, New York, NY, USA, 1247-1258. DOI=10.1145/2588555.2595628
• [R8] (Energy Efficiency)
  A survey on techniques for improving the energy efficiency of large-scale distributed systems, Anne-Cecile Orgerie, Marcos Dias de Assuncao, and Laurent Lefevre. 2014. ACM Comput. Surv. 46, 4, Article 47 (March 2014), 31 pages. DOI=10.1145/2532637
• [R9] (Storage)
  A Survey and Classification of Storage Deduplication Systems, João Paulo and José Pereira. 2014. ACM Comput. Surv. 47, 1, Article 11 (June 2014), 30 pages. DOI=10.1145/2611778