{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:59:29Z","timestamp":1732042769493},"reference-count":102,"publisher":"Association for Computing Machinery (ACM)","issue":"1","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2024,1,31]]},"abstract":"Data is a precious resource in today\u2019s society, and it is generated at an unprecedented and constantly growing pace. The need to store, analyze, and make data promptly available to a multitude of users introduces formidable challenges in modern software platforms. These challenges radically impacted the research fields that gravitate around data management and processing, with the introduction of distributed data-intensive systems that offer innovative programming models and implementation strategies to handle data characteristics such as its volume, the rate at which it is produced, its heterogeneity, and its distribution. Each data-intensive system brings its specific choices in terms of data model, usage assumptions, synchronization, processing strategy, deployment, guarantees in terms of consistency, fault tolerance, and ordering. Yet, the problems data-intensive systems face and the solutions they propose are frequently overlapping. This article proposes a unifying model that dissects the core functionalities of data-intensive systems, and discusses alternative design and implementation strategies, pointing out their assumptions and implications. The model offers a common ground to understand and compare highly heterogeneous solutions, with the potential of fostering cross-fertilization across research communities. We apply our model by classifying tens of systems: an exercise that brings to interesting observations on the current trends in the domain of data-intensive systems and suggests open research directions.<\/jats:p>","DOI":"10.1145\/3604801","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T12:08:53Z","timestamp":1686830933000},"page":"1-69","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["A Model and Survey of Distributed Data-Intensive Systems"],"prefix":"10.1145","volume":"56","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-0023-8639","authenticated-orcid":false,"given":"Alessandro","family":"Margara","sequence":"first","affiliation":[{"name":"Politecnico di Milano, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-0921-7383","authenticated-orcid":false,"given":"Gianpaolo","family":"Cugola","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3555-7760","authenticated-orcid":false,"given":"Nicol\u00f2","family":"Felicioni","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0009-0005-9919-2587","authenticated-orcid":false,"given":"Stefano","family":"Cilloni","sequence":"additional","affiliation":[{"name":"Politecnico di Milano, Italy"}]}],"member":"320","published-online":{"date-parts":[[2023,8,26]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"Proceedings of OSDI 2016","author":"Abadi M.","year":"2016","unstructured":"M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, et\u00a0al. 2016. TensorFlow: A system for large-scale machine learning. In Proceedings of OSDI 2016."},{"issue":"1","key":"e_1_3_3_3_2","doi-asserted-by":"crossref","DOI":"10.14778\/1687627.1687731","article-title":"HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads","volume":"2","author":"Abouzeid A.","year":"2009","unstructured":"A. Abouzeid, K. Bajda-Pawlikowski, D. Abadi, A. Silberschatz, and A. Rasin. 2009. HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads. Proceedings of the VLDB Endowment 2, 1 (2009), 922\u2013933.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"12","key":"e_1_3_3_4_2","doi-asserted-by":"crossref","DOI":"10.14778\/3181-3194","article-title":"Monarch: Google\u2019s planet-scale in-memory time series database","volume":"13","author":"Adams C.","year":"2020","unstructured":"C. Adams, L. Alonso, B. Atkin, J. Banning, S. Bhola, R. Buskens, M. Chen, et\u00a0al. 2020. Monarch: Google\u2019s planet-scale in-memory time series database. Proceedings of the VLDB Endowment 13, 12 (2020), 3181\u20133194.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_5_2","volume-title":"Proceedings of ICDE 2000","author":"Adya A.","year":"2000","unstructured":"A. Adya, B. Liskov, and P. O\u2019Neil. 2000. Generalized isolation level definitions. In Proceedings of ICDE 2000. IEEE, Los Alamitos, CA."},{"key":"e_1_3_3_6_2","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpdc.2020.03.003","article-title":"TSpoon: Transactions on a stream processor","volume":"140","author":"Affetti L.","year":"2020","unstructured":"L. Affetti, A. Margara, and G. Cugola. 2020. TSpoon: Transactions on a stream processor. Journal of Parallel and Distributed Computing 140 (2020), 65\u201379.","journal-title":"Journal of Parallel and Distributed Computing"},{"key":"e_1_3_3_7_2","volume-title":"Proceedings of HotOS 2015","author":"Ajoux P.","year":"2015","unstructured":"P. Ajoux, N. Bronson, S. Kumar, W. Lloyd, and K. Veeraraghavan. 2015. Challenges to adopting stronger consistency at scale. In Proceedings of HotOS 2015."},{"issue":"11","key":"e_1_3_3_8_2","doi-asserted-by":"crossref","DOI":"10.14778\/2536222.2536229","article-title":"MillWheel: Fault-tolerant stream processing at Internet scale","volume":"6","author":"Akidau T.","year":"2013","unstructured":"T. Akidau, A. Balikov, K. Bekiro\u011flu, S. Chernyak, J. Haberman, R. Lax, S. McVeety, D. Mills, P. Nordstrom, and S. Whittle. 2013. MillWheel: Fault-tolerant stream processing at Internet scale. Proceedings of the VLDB Endowment 6, 11 (2013), 1033\u20131044.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"12","key":"e_1_3_3_9_2","doi-asserted-by":"crossref","DOI":"10.14778\/2824032.2824076","article-title":"The dataflow model: A practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing","volume":"8","author":"Akidau T.","year":"2015","unstructured":"T. Akidau, R. Bradshaw, C. Chambers, S. Chernyak, R. J. Fern\u00e1ndez-Moctezuma, R. Lax, S. McVeety, et\u00a0al. 2015. The dataflow model: A practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing. Proceedings of the VLDB Endowment 8, 12 (2015), 1792\u20131803.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"14","key":"e_1_3_3_10_2","doi-asserted-by":"crossref","DOI":"10.14778\/2733085.2733096","article-title":"AsterixDB: A scalable, open source BDMS","volume":"7","author":"Alsubaiee S.","year":"2014","unstructured":"S. Alsubaiee, Y. Altowim, H. Altwaijry, A. Behm, V. Borkar, Y. Bu, M. Carey, et\u00a0al. 2014. AsterixDB: A scalable, open source BDMS. Proceedings of the VLDB Endowment 7, 14 (2014).","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_11_2","volume-title":"CouchDB: The Definitive Guide: Time to Relax","author":"Anderson J. C.","year":"2010","unstructured":"J. C. Anderson, J. Lehnardt, and N. Slater. 2010. CouchDB: The Definitive Guide: Time to Relax. O\u2019Reilly Media."},{"key":"e_1_3_3_12_2","volume-title":"Proceedings of SIGMOD 2019","author":"Antonopoulos P.","year":"2019","unstructured":"P. Antonopoulos, A. Budovski, C. Diaconu, A. Hernandez Saenz, J. Hu, H. Kodavalla, D. Kossmann, et\u00a0al. 2019. Socrates: The new SQL server in the cloud. In Proceedings of SIGMOD 2019. ACM, New York, NY."},{"key":"e_1_3_3_13_2","volume-title":"Proceedings of SIGMOD 2015","author":"Armbrust M.","year":"2015","unstructured":"M. Armbrust, R. S. Xin, C. Lian, Y. Huai, D. Liu, J. K. Bradley, X. Meng, et\u00a0al. 2015. Spark SQL: Relational data processing in spark. In Proceedings of SIGMOD 2015. ACM, New York, NY."},{"key":"e_1_3_3_14_2","volume-title":"Proceedings of SIGMOD 2017","author":"Arulraj J.","year":"2017","unstructured":"J. Arulraj and A. Pavlo. 2017. How to build a non-volatile memory database management system. In Proceedings of SIGMOD 2017. ACM, New York, NY."},{"key":"e_1_3_3_15_2","volume-title":"Proceedings of SIGMOD 2017","author":"Bacon D. F.","year":"2017","unstructured":"D. F. Bacon, N. Bales, N. Bruno, B. F. Cooper, A. Dickinson, A. Fikes, C. Fraser, et\u00a0al. 2017. Spanner: Becoming a SQL system. In Proceedings of SIGMOD 2017. ACM, New York, NY."},{"issue":"3","key":"e_1_3_3_16_2","doi-asserted-by":"crossref","DOI":"10.14778\/2732232.2732237","article-title":"Highly available transactions: Virtues and limitations","volume":"7","author":"Bailis P.","year":"2013","unstructured":"P. Bailis, A. Davidson, A. Fekete, A. Ghodsi, J. M. Hellerstein, and I. Stoica. 2013. Highly available transactions: Virtues and limitations. Proceedings of the VLDB Endowment 7, 3 (2013), 181\u2013192.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_17_2","volume-title":"Proceedings of SOSP 2013","author":"Balakrishnan M.","year":"2013","unstructured":"M. Balakrishnan, D. Malkhi, T. Wobber, M. Wu, V. Prabhakaran, M. Wei, J. D. Davis, S. Rao, T. Zou, and A. Zuck. 2013. Tango: Distributed data structures over a shared log. In Proceedings of SOSP 2013. ACM, New York, NY."},{"issue":"8","key":"e_1_3_3_18_2","doi-asserted-by":"crossref","DOI":"10.1109\/TSE.2019.2931537","article-title":"Fine-grained dynamic resource allocation for big-data applications","volume":"47","author":"Baresi L.","year":"2021","unstructured":"L. Baresi, A. Leva, and G. Quattrocchi. 2021. Fine-grained dynamic resource allocation for big-data applications. IEEE Transactions on Software Engineering 47, 8 (2021), 1668\u20131682.","journal-title":"IEEE Transactions on Software Engineering"},{"key":"e_1_3_3_19_2","volume-title":"Kafka Streams in Action: Real-Time Apps and Microservices with the Kafka Streams API","author":"Bejeck B.","year":"2018","unstructured":"B. Bejeck. 2018. Kafka Streams in Action: Real-Time Apps and Microservices with the Kafka Streams API. Manning."},{"key":"e_1_3_3_20_2","volume-title":"Proceedings of ICDE 2011","author":"Borkar V.","year":"2011","unstructured":"V. Borkar, M. Carey, R. Grover, N. Onose, and R. Vernica. 2011. Hyracks: A flexible and extensible foundation for data-intensive computing. In Proceedings of ICDE 2011. IEEE, Los Alamitos, CA."},{"key":"e_1_3_3_21_2","volume-title":"Proceedings of ATC 2013","author":"Bronson N.","year":"2013","unstructured":"N. Bronson, Z. Amsden, G. Cabrera, P. Chakka, P. Dimov, H. Ding, J. Ferris, et\u00a0al. 2013. TAO: Facebook\u2019s distributed data store for the social graph. In Proceedings of ATC 2013."},{"issue":"1","key":"e_1_3_3_22_2","article-title":"HaLoop: Efficient iterative data processing on large clusters","volume":"3","author":"Bu Y.","year":"2010","unstructured":"Y. Bu, B. Howe, M. Balazinska, and M. D. Ernst. 2010. HaLoop: Efficient iterative data processing on large clusters. Proceedings of the VLDB Endowment 3, 1-2 (2010), 285\u2013296.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_23_2","volume-title":"Proceedings of SIGMOD 2020","author":"Buragohain C.","year":"2020","unstructured":"C. Buragohain, K. M. Risvik, P. Brett, M. Castro, W. Cho, J. Cowhig, N. Gloy, et\u00a0al. 2020. A1: A distributed in-memory graph database. In Proceedings of SIGMOD 2020. ACM, New York, NY."},{"key":"e_1_3_3_24_2","volume-title":"Proceedings of SIGMOD 2019","author":"Camacho-Rodr\u00edguez J.","year":"2019","unstructured":"J. Camacho-Rodr\u00edguez, A. Chauhan, A. Gates, E. Koifman, O. O\u2019Malley, V. Garg, Z. Haindrich, et\u00a0al. 2019. Apache Hive: From MapReduce to enterprise-grade big data warehousing. In Proceedings of SIGMOD 2019. ACM, New York, NY."},{"issue":"4","key":"e_1_3_3_25_2","article-title":"Apache Flink\u2122: Stream and batch processing in a single engine","volume":"38","author":"Carbone P.","year":"2015","unstructured":"P. Carbone, A. Katsifodimos, S. Ewen, V. Markl, S. Haridi, and K. Tzoumas. 2015. Apache Flink\u2122: Stream and batch processing in a single engine. Data Engineering Bulletin 38, 4 (2015), 28\u201338.","journal-title":"Data Engineering Bulletin"},{"key":"e_1_3_3_26_2","doi-asserted-by":"crossref","DOI":"10.1145\/3514496","article-title":"Run-time adaptation of data stream processing systems: The state of the art","author":"Cardellini V.","year":"2022","unstructured":"V. Cardellini, F. Lo Presti, M. Nardelli, and G. Russo Russo. 2022. Run-time adaptation of data stream processing systems: The state of the art. ACM Computing Surveys 54, 11s (2022), Article 237, 36 pages.","journal-title":"ACM Computing Surveys"},{"key":"e_1_3_3_27_2","volume-title":"Proceedings of SIGMOD 2013","author":"Fernandez R. Castro","year":"2013","unstructured":"R. Castro Fernandez, M. Migliavacca, E. Kalyvianaki, and P. Pietzuch. 2013. Integrating scale out and fault tolerance in stream processing using operator state management. In Proceedings of SIGMOD 2013. ACM, New York, NY."},{"issue":"13","key":"e_1_3_3_28_2","doi-asserted-by":"crossref","DOI":"10.14778\/2733004.2733048","article-title":"S-Store: A streaming NewSQL system for big velocity applications","volume":"7","author":"Cetintemel U.","year":"2014","unstructured":"U. Cetintemel, J. Du, T. Kraska, S. Madden, D. Maier, J. Meehan, A. Pavlo, M. Stonebraker, E. Sutherland, and N. Tatbul. 2014. S-Store: A streaming NewSQL system for big velocity applications. Proceedings of the VLDB Endowment 7, 13 (2014), 1633\u20131636.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"1","key":"e_1_3_3_29_2","doi-asserted-by":"crossref","DOI":"10.1145\/214451.214456","article-title":"Distributed snapshots: Determining global states of distributed systems","volume":"3","author":"Chandy K. M.","year":"1985","unstructured":"K. M. Chandy and L. Lamport. 1985. Distributed snapshots: Determining global states of distributed systems. ACM Transactions on Computer Systems 3, 1 (1985), 63\u201375.","journal-title":"ACM Transactions on Computer Systems"},{"key":"e_1_3_3_30_2","doi-asserted-by":"crossref","unstructured":"F. Chang J. Dean S. Ghemawat W. C. Hsieh D. A. Wallach M. Burrows T. Chandra A. Fikes and R. Gruber. 2008. Bigtable: A distributed storage system for structured data. ACM Transactions on Computer Systems 26 2 (2008) Article 4 26 pages.","DOI":"10.1145\/1365815.1365816"},{"key":"e_1_3_3_31_2","volume-title":"Proceedings of EuroSys 2018","author":"Chen H.","year":"2018","unstructured":"H. Chen, M. Liu, Y. Zhao, X. Yan, D. Yan, and J. Cheng. 2018. G-Miner: An efficient task-oriented graph mining system. In Proceedings of EuroSys 2018. ACM, New York, NY."},{"key":"e_1_3_3_32_2","volume-title":"Proceedings of SCC 2018","author":"Chen H.","year":"2018","unstructured":"H. Chen and M. Migliavacca. 2018. StreamDB: A unified data management system for service-based cloud application. In Proceedings of SCC 2018. IEEE, Los Alamitos, CA."},{"key":"e_1_3_3_33_2","volume-title":"MongoDB: The Definitive Guide: Powerful and Scalable Data Storage","author":"Chodorow K.","year":"2013","unstructured":"K. Chodorow. 2013. MongoDB: The Definitive Guide: Powerful and Scalable Data Storage. O\u2019Reilly Media."},{"issue":"2","key":"e_1_3_3_34_2","doi-asserted-by":"crossref","DOI":"10.14778\/1454159.1454167","article-title":"PNUTS: Yahoo!\u2019s hosted data serving platform","volume":"1","author":"Cooper B. F.","year":"2008","unstructured":"B. F. Cooper, R. Ramakrishnan, U. Srivastava, A. Silberstein, P. Bohannon, H. A. Jacobsen, N. Puz, D. Weaver, and R. Yerneni. 2008. PNUTS: Yahoo!\u2019s hosted data serving platform. Proceedings of the VLDB Endowment 1, 2 (2008), 1277\u20131288.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"3","key":"e_1_3_3_35_2","doi-asserted-by":"crossref","DOI":"10.1145\/2491245","article-title":"Spanner: Google\u2019s globally distributed database","volume":"31","author":"Corbett J. C.","year":"2013","unstructured":"J. C. Corbett, J. Dean, M. Epstein, A. Fikes, C. Frost, J. J. Furman, S. Ghemawat, et\u00a0al. 2013. Spanner: Google\u2019s globally distributed database. ACM Transactions on Computer Systems 31, 3 (2013), Article 8, 22 pages.","journal-title":"ACM Transactions on Computer Systems"},{"issue":"11","key":"e_1_3_3_36_2","doi-asserted-by":"crossref","DOI":"10.14778\/2536222.2536239","article-title":"Unicorn: A system for searching the social graph","volume":"6","author":"Curtiss M.","year":"2013","unstructured":"M. Curtiss, I. Becker, T. Bosman, S. Doroshenko, L. Grijincu, T. Jackson, S. Kunnatur, et\u00a0al. 2013. Unicorn: A system for searching the social graph. Proceedings of the VLDB Endowment 6, 11 (2013), 1150\u20131161.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"2","key":"e_1_3_3_37_2","doi-asserted-by":"crossref","DOI":"10.1145\/3158661","article-title":"A survey on NoSQL stores","volume":"51","author":"Davoudian A.","year":"2018","unstructured":"A. Davoudian, L. Chen, and M. Liu. 2018. A survey on NoSQL stores. ACM Computing Surveys 51, 2 (2018), Article 40, 43 pages.","journal-title":"ACM Computing Surveys"},{"issue":"5","key":"e_1_3_3_38_2","doi-asserted-by":"crossref","DOI":"10.1145\/3408314","article-title":"Big data systems: A software engineering perspective","volume":"53","author":"Davoudian A.","year":"2020","unstructured":"A. Davoudian and M. Liu. 2020. Big data systems: A software engineering perspective. ACM Computing Surveys 53, 5 (2020), Article 110, 39 pages.","journal-title":"ACM Computing Surveys"},{"issue":"1","key":"e_1_3_3_39_2","doi-asserted-by":"crossref","DOI":"10.1145\/1327452.1327492","article-title":"MapReduce: Simplified data processing on large clusters","volume":"51","author":"Dean J.","year":"2008","unstructured":"J. Dean and S. Ghemawat. 2008. MapReduce: Simplified data processing on large clusters. Communications of the ACM 51, 1 (2008), 107\u2013113.","journal-title":"Communications of the ACM"},{"key":"e_1_3_3_40_2","volume-title":"Proceedings of SOSP","author":"DeCandia G.","year":"2007","unstructured":"G. DeCandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, P. Vosshall, and W. Vogels. 2007. Dynamo: Amazon\u2019s highly available key-value store. In Proceedings of SOSP2007. ACM, New York, NY."},{"key":"e_1_3_3_41_2","first-page":"1078","volume-title":"Proceedings of SIGMOD 2022","author":"Monte Bonaventura Del","year":"2022","unstructured":"Bonaventura Del Monte, Steffen Zeuch, Tilmann Rabl, and Volker Markl. 2022. Rethinking stateful stream processing with RDMA. In Proceedings of SIGMOD 2022. ACM, New York, NY, 1078\u20131092."},{"key":"e_1_3_3_42_2","volume-title":"Proceedings of NSDI 2014","author":"Dragojevi\u0107 A.","year":"2014","unstructured":"A. Dragojevi\u0107, D. Narayanan, M. Castro, and O. Hodson. 2014. FaRM: Fast remote memory. In Proceedings of NSDI 2014."},{"issue":"1","key":"e_1_3_3_43_2","article-title":"In-memory database acceleration on FPGAs: A survey","volume":"29","author":"Fang J.","year":"2020","unstructured":"J. Fang, Y. Mulder, J. Hidders, J. Lee, and H. P. Hofstee. 2020. In-memory database acceleration on FPGAs: A survey. VLDP Journal 29, 1 (2020), 33\u201359.","journal-title":"VLDP Journal"},{"key":"e_1_3_3_44_2","volume-title":"Proceedings of ATC 2014","author":"Fernandez R. C.","year":"2014","unstructured":"R. C. Fernandez, M. Migliavacca, E. Kalyvianaki, and P. Pietzuch. 2014. Making state explicit for imperative big data processing. In Proceedings of ATC 2014."},{"issue":"9","key":"e_1_3_3_45_2","doi-asserted-by":"crossref","DOI":"10.1145\/3477602","article-title":"Handling iterations in distributed dataflow systems","volume":"54","author":"G\u00e9vay G. E.","year":"2021","unstructured":"G. E. G\u00e9vay, J. Soto, and V. Markl. 2021. Handling iterations in distributed dataflow systems. ACM Computing Surveys 54, 9 (2021), Article 199, 38 pages.","journal-title":"ACM Computing Surveys"},{"key":"e_1_3_3_46_2","volume-title":"Proceedings of OSDI 2012","author":"Gonzalez J. E.","year":"2012","unstructured":"J. E. Gonzalez, Y. Low, H. Gu, D. Bickson, and C. Guestrin. 2012. PowerGraph: Distributed graph-parallel computation on natural graphs. In Proceedings of OSDI 2012."},{"key":"e_1_3_3_47_2","volume-title":"Proceedings of OSDI 2014","author":"Gonzalez J. E.","year":"2014","unstructured":"J. E. Gonzalez, R. S. Xin, A. Dave, D. Crankshaw, M. J. Franklin, and I. Stoica. 2014. GraphX: Graph processing in a distributed dataflow framework. In Proceedings of OSDI 2014."},{"issue":"1","key":"e_1_3_3_48_2","doi-asserted-by":"crossref","DOI":"10.1145\/3408895","article-title":"StreamGen: Model-driven development of distributed streaming applications","volume":"30","author":"Guerriero M.","year":"2021","unstructured":"M. Guerriero, D. A. Tamburri, and E. Di Nitto. 2021. StreamGen: Model-driven development of distributed streaming applications. ACM Transactions on Software Engineering and Methodology 30, 1 (2021), Article 1, 30 pages.","journal-title":"ACM Transactions on Software Engineering and Methodology"},{"issue":"4","key":"e_1_3_3_49_2","doi-asserted-by":"crossref","DOI":"10.1145\/2528412","article-title":"A catalog of stream processing optimizations","volume":"46","author":"Hirzel M.","year":"2014","unstructured":"M. Hirzel, R. Soul\u00e9, S. Schneider, B. Gedik, and R. Grimm. 2014. A catalog of stream processing optimizations. ACM Computing Surveys 46, 4 (2014), Article 46, 34 pages.","journal-title":"ACM Computing Surveys"},{"issue":"2","key":"e_1_3_3_50_2","doi-asserted-by":"crossref","DOI":"10.1109\/MCAS.2021.3071608","article-title":"FPGA acceleration for big data analytics: Challenges and opportunities","volume":"21","author":"Hoozemans J.","year":"2021","unstructured":"J. Hoozemans, J. Peltenburg, F. Nonnemacher, A. Hadnagy, Z. Al-Ars, and H. P. Hofstee. 2021. FPGA acceleration for big data analytics: Challenges and opportunities. IEEE Circuits and Systems Magazine 21, 2 (2021), 30\u201347.","journal-title":"IEEE Circuits and Systems Magazine"},{"key":"e_1_3_3_51_2","volume-title":"Proceedings of ATC 2019","author":"Huang Y.","year":"2019","unstructured":"Y. Huang, X. Yan, G. Jiang, T. Jin, J. Cheng, A. Xu, Z. Liu, and S. Tu. 2019. Tangram: Bridging immutable and mutable abstractions for distributed data analytics. In Proceedings of ATC 2019."},{"key":"e_1_3_3_52_2","volume-title":"Proceedings of EuroSys 2007","author":"Isard M.","year":"2007","unstructured":"M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly. 2007. Dryad: Distributed data-parallel programs from sequential building blocks. In Proceedings of EuroSys 2007. ACM, New York, NY."},{"issue":"11","key":"e_1_3_3_53_2","doi-asserted-by":"crossref","DOI":"10.1109\/TKDE.2017.2740932","article-title":"Time series management systems: A survey","volume":"29","author":"Jensen S. K.","year":"2017","unstructured":"S. K. Jensen, T. B. Pedersen, and C. Thomsen. 2017. Time series management systems: A survey. IEEE Transactions on Knowledge and Data Engineering 29, 11 (2017), 2581\u20132600.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"12","key":"e_1_3_3_54_2","doi-asserted-by":"crossref","DOI":"10.14778\/3415478.3415550","article-title":"Alibaba Hologres: A cloud-native service for hybrid serving\/analytical processing","volume":"13","author":"Jiang X.","year":"2020","unstructured":"X. Jiang, Y. Hu, Y. Xiang, G. Jiang, X. Jin, C. Xia, W. Jiang, et\u00a0al. 2020. Alibaba Hologres: A cloud-native service for hybrid serving\/analytical processing. Proceedings of the VLDB Endowment 13, 12 (2020), 3272\u20133284.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_55_2","volume-title":"Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems","author":"Kleppmann M.","year":"2016","unstructured":"M. Kleppmann. 2016. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O\u2019Reilly Media."},{"key":"e_1_3_3_56_2","volume-title":"Proceedings of NetDB 2011","author":"Kreps J.","year":"2011","unstructured":"J. Kreps, N. Narkhede, and J. Rao. 2011. Kafka: A distributed messaging system for log processing. In Proceedings of NetDB 2011."},{"key":"e_1_3_3_57_2","volume-title":"Proceedings of SIGMOD 2015","author":"Kulkarni S.","year":"2015","unstructured":"S. Kulkarni, N. Bhagat, M. Fu, V. Kedigehalli, C. Kellogg, S. Mittal, J. M. Patel, K. Ramasamy, and S. Taneja. 2015. Twitter Heron: Stream processing at scale. In Proceedings of SIGMOD 2015. ACM, New York, NY."},{"issue":"2","key":"e_1_3_3_58_2","doi-asserted-by":"crossref","DOI":"10.1145\/1773912.1773922","article-title":"Cassandra: A decentralized structured storage system","volume":"44","author":"Lakshman A.","year":"2010","unstructured":"A. Lakshman and P. Malik. 2010. Cassandra: A decentralized structured storage system. ACM SIGOPS Operating Systems Review 44, 2 (2010), 35\u201340.","journal-title":"ACM SIGOPS Operating Systems Review"},{"issue":"12","key":"e_1_3_3_59_2","article-title":"The art of balance: A RateupDB experience of building a CPU\/GPU hybrid database product","volume":"14","author":"Lee R.","year":"2021","unstructured":"R. Lee, M. Zhou, C. Li, S. Hu, J. Teng, D. Li, and X. Zhang. 2021. The art of balance: A RateupDB experience of building a CPU\/GPU hybrid database product. Proceedings of the VLDB Endowment 14, 12 (2021), 2999\u20133013.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_60_2","volume-title":"Proceedings of CIDR 2011","author":"Levandoski Justin","year":"2011","unstructured":"Justin Levandoski, David Lomet, and Kevin Keliang Zhao. 2011. Deuteronomy: Transaction support for cloud data. In Proceedings of CIDR 2011."},{"issue":"5","key":"e_1_3_3_61_2","article-title":"The lambda and the kappa","volume":"21","author":"Lin J.","year":"2017","unstructured":"J. Lin. 2017. The lambda and the kappa. IEEE Internet Computing 21, 5 (2017), 60\u201366.","journal-title":"IEEE Internet Computing"},{"issue":"5","key":"e_1_3_3_62_2","article-title":"Zen: A high-throughput log-free OLTP engine for non-volatile main memory","volume":"14","author":"Liu G.","year":"2021","unstructured":"G. Liu, L. Chen, and S. Chen. 2021. Zen: A high-throughput log-free OLTP engine for non-volatile main memory. Proceedings of the VLDB Endowment 14, 5 (2021), 835\u2013848.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"8","key":"e_1_3_3_63_2","article-title":"Distributed GraphLab: A framework for machine learning and data mining in the cloud","volume":"5","author":"Low Y.","year":"2012","unstructured":"Y. Low, D. Bickson, J. Gonzalez, C. Guestrin, A. Kyrola, and J. M. Hellerstein. 2012. Distributed GraphLab: A framework for machine learning and data mining in the cloud. Proceedings of the VLDB Endowment 5, 8 (2012), 716\u2013727.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"3","key":"e_1_3_3_64_2","article-title":"Multi-model databases: A new journey to handle the variety of data","volume":"52","author":"Lu J.","year":"2019","unstructured":"J. Lu and I. Holubov\u00e1. 2019. Multi-model databases: A new journey to handle the variety of data. ACM Computing Surveys 52, 3 (2019), Article 55, 38 pages.","journal-title":"ACM Computing Surveys"},{"key":"e_1_3_3_65_2","volume-title":"Redis Cookbook: Practical Techniques for Fast Data Manipulation","author":"Macedo T.","year":"2011","unstructured":"T. Macedo and F. Oliveira. 2011. Redis Cookbook: Practical Techniques for Fast Data Manipulation. O\u2019Reilly Media."},{"issue":"5","key":"e_1_3_3_66_2","doi-asserted-by":"crossref","DOI":"10.14778\/3303753.3303765","article-title":"Unifying consensus and atomic commitment for effective cloud data management","volume":"12","author":"Maiyya S.","year":"2019","unstructured":"S. Maiyya, F. Nawab, D. Agrawal, and A. El Abbadi. 2019. Unifying consensus and atomic commitment for effective cloud data management. Proceedings of the VLDB Endowment 12, 5 (2019), 611\u2013623.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_67_2","volume-title":"Proceedings of SIGMOD 2010","author":"Malewicz G.","year":"2010","unstructured":"G. Malewicz, M. H. Austern, A. J. C. Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski. 2010. Pregel: A system for large-scale graph processing. In Proceedings of SIGMOD 2010. ACM, New York, NY."},{"key":"e_1_3_3_68_2","volume-title":"Proceedings of ICDE 2014","author":"Malviya N.","year":"2014","unstructured":"N. Malviya, A. Weisberg, S. Madden, and M. Stonebraker. 2014. Rethinking main memory OLTP recovery. In Proceedings of ICDE 2014. IEEE, Los Alamitos, CA."},{"issue":"2","key":"e_1_3_3_69_2","article-title":"Thinking like a vertex: A survey of vertex-centric frameworks for large-scale distributed graph processing","volume":"48","author":"McCune R. Ryan","year":"2015","unstructured":"R. Ryan McCune, T. Weninger, and G. Madey. 2015. Thinking like a vertex: A survey of vertex-centric frameworks for large-scale distributed graph processing. ACM Computing Surveys 48, 2 (2015), Article 25, 39 pages.","journal-title":"ACM Computing Surveys"},{"issue":"1","key":"e_1_3_3_70_2","article-title":"MLlib: Machine learning in apache spark","volume":"17","author":"Meng X.","year":"2016","unstructured":"X. Meng, J. Bradley, B. Yavuz, E. Sparks, S. Venkataraman, D. Liu, J. Freeman, et\u00a0al. 2016. MLlib: Machine learning in apache spark. Journal of Machine Learning Research 17, 1 (2016), 1235\u20131241.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_3_71_2","volume-title":"Proceedings of CIDR 2017","author":"Mozafari B.","year":"2017","unstructured":"B. Mozafari, J. Ramnarayan, S. Menon, Y. Mahajan, S. Chakraborty, H. Bhanawat, and K. Bachhav. 2017. SnappyData: A unified cluster for streaming, transactions and interactive analytics. In Proceedings of CIDR 2017."},{"key":"e_1_3_3_72_2","volume-title":"Proceedings of SOSP 2013","author":"Murray D. G.","year":"2013","unstructured":"D. G. Murray, F. McSherry, R. Isaacs, M. Isard, P. Barham, and M. Abadi. 2013. Naiad: A timely dataflow system. In Proceedings of SOSP 2013. ACM, New York, NY."},{"key":"e_1_3_3_73_2","volume-title":"Proceedings of NSDI 2011","author":"Murray D. G.","year":"2011","unstructured":"D. G. Murray, M. Schwarzkopf, C. Smowton, S. Smith, A. Madhavapeddy, and S. Hand. 2011. CIEL: A universal execution engine for distributed data-flow computing. In Proceedings of NSDI 2011."},{"key":"e_1_3_3_74_2","volume-title":"Proceedings of NSDI 2013","author":"Nishtala R.","year":"2013","unstructured":"R. Nishtala, H. Fugal, S. Grimm, M. Kwiatkowski, H. Lee, H. C. Li, R. McElroy, et\u00a0al. 2013. Scaling memcache at Facebook. In Proceedings of NSDI 2013."},{"issue":"12","key":"e_1_3_3_75_2","doi-asserted-by":"crossref","DOI":"10.14778\/3137765.3137770","article-title":"Samza: Stateful scalable stream processing at LinkedIn","volume":"10","author":"Noghabi S. A.","year":"2017","unstructured":"S. A. Noghabi, K. Paramasivam, Y. Pan, N. Ramesh, J. Bringhurst, I. Gupta, and R. H. Campbell. 2017. Samza: Stateful scalable stream processing at LinkedIn. Proceedings of the VLDB Endowment 10, 12 (2017), 1634\u20131645.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"12","key":"e_1_3_3_76_2","doi-asserted-by":"crossref","DOI":"10.14778\/2824032.2824078","article-title":"Gorilla: A fast, scalable, in-memory time series database","volume":"8","author":"Pelkonen T.","year":"2015","unstructured":"T. Pelkonen, S. Franklin, J. Teller, P. Cavallaro, Q. Huang, J. Meza, and K. Veeraraghavan. 2015. Gorilla: A fast, scalable, in-memory time series database. Proceedings of the VLDB Endowment 8, 12 (2015), 1816\u20131827.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_3_3_77_2","volume-title":"Proceedings of OSDI 2010","author":"Peng D.","year":"2010","unstructured":"D. Peng and F. Dabek. 2010. Large-scale incremental processing using distributed transactions and notifications. In Proceedings of OSDI 2010."},{"issue":"2","key":"e_1_3_3_78_2","doi-asserted-by":"crossref","DOI":"10.1145\/3303849","article-title":"A comprehensive survey on parallelization and elasticity in stream processing","volume":"52","author":"R\u00f6ger H.","year":"2019","unstructured":"H. R\u00f6ger and R. Mayer. 2019. A comprehensive survey on parallelization and elasticity in stream processing. ACM Computing Surveys 52, 2 (2019), Article 36, 37 pages.","journal-title":"ACM Computing Surveys"},{"key":"e_1_3_3_79_2","volume-title":"Proceedings of BIRTE 2018","author":"Sax M. J.","year":"2018","unstructured":"M. J. Sax, G. Wang, M. Weidlich, and J. C. Freytag. 2018. Streams and tables: Two sides of the same coin. In Proceedings of BIRTE 2018. ACM, New York, NY."},{"key":"e_1_3_3_80_2","volume-title":"Proceedings of SIGMOD 2018","author":"Shah V.","year":"2018","unstructured":"V. Shah and M. Antonio Vaz Salles. 2018. Reactors: A case for predictable, virtualized actor database systems. In Proceedings of SIGMOD 2018. ACM, New York, NY."},{"key":"e_1_3_3_81_2","volume-title":"Proceedings of SIGMOD","author":"Shao B.","year":"2013","unstructured":"B. Shao, H. Wang, and Y. Li. 2013. Trinity: A distributed graph engine on a memory cloud. In Proceedings of SIGMOD2013. ACM, New York, NY."},{"key":"e_1_3_3_82_2","volume-title":"Stabilization, Safety, and Security of Distributed Systems","author":"Shapiro M.","year":"2011","unstructured":"M. Shapiro, N. Pregui\u00e7a, C. Baquero, and M. Zawirski. 2011. Conflict-free replicated data types. In Stabilization, Safety, and Security of Distributed Systems. Lecture Notes in Computer Science, Vol. 6976. Springer, 386\u2013400."},{"issue":"5","key":"e_1_3_3_83_2","article-title":"Edge computing: Vision and challenges","volume":"3","author":"Shi W.","year":"2016","unstructured":"W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu. 2016. Edge computing: Vision and challenges. IEEE Internet of Things Journal 3, 5 (2016), 637\u2013646.","journal-title":"IEEE Internet of Things Journal"},{"issue":"11","key":"e_1_3_3_84_2","doi-asserted-by":"crossref","DOI":"10.14778\/2536222.2536232","article-title":"F1: A distributed SQL database that scales","volume":"6","author":"Shute J.","year":"2013","unstructured":"J. Shute, R. Vingralek, B. Samwel, B. Handy, C. Whipkey, E. Rollins, M. Oancea, et\u00a0al. 2013. F1: A distributed SQL database that scales. Proceedings of the VLDB Endowment 6, 11 (2013), 1068\u20131079.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"13","key":"e_1_3_3_85_2","doi-asserted-by":"crossref","DOI":"10.14778\/3007263.3007276","article-title":"Aerospike: Architecture of a real-time operational DBMS","volume":"9","author":"Srinivasan V.","year":"2016","unstructured":"V. Srinivasan, B. Bulkowski, W. L. Chu, S. Sayyaparaju, A. Gooding, R. Iyer, A. Shinde, and T. Lopatic. 2016. Aerospike: Architecture of a real-time operational DBMS. Proceedings of the VLDB Endowment 9, 13 (2016), 1389\u20131400.","journal-title":"Proceedings of the VLDB Endowment"},{"issue":"4","key":"e_1_3_3_86_2","doi-asserted-by":"crossref","DOI":"10.1145\/1721654.1721659","article-title":"SQL databases v. NoSQL databases","volume":"53","author":"Stonebraker M.","year":"2010","unstructured":"M. Stonebraker. 2010. SQL databases v. NoSQL databases. Communications of the ACM 53, 4 (2010), 10\u201311.","journal-title":"Communications of the ACM"},{"issue":"11","key":"e_1_3_3_87_2","doi-asserted-by":"crossref","DOI":"10.1145\/2366316.2366319","article-title":"New opportunities for new SQL","volume":"55","author":"Stonebraker M.","year":"2012","unstructured":"M. Stonebraker. 2012. New opportunities for new SQL. Communications of the ACM 55, 11 (2012), 10-11.","journal-title":"Communications of the ACM"},{"key":"e_1_3_3_88_2","volume-title":"Proceedings of ICDE 2005","author":"Stonebraker M.","year":"2005","unstructured":"M. Stonebraker and U. Cetintemel. 2005. \u201cOne size fits all\u201d: An idea whose time has come and gone. In Proceedings of ICDE 2005. IEEE, Los Alamitos, CA."},{"key":"e_1_3_3_89_2","volume-title":"Proceedings of VLDB 2007","author":"Stonebraker M.","year":"2007","unstructured":"M. Stonebraker, S. Madden, D. J. Abadi, S. Harizopoulos, N. Hachem, and P. Helland. 2007. The end of an architectural era: (It\u2019s time for a complete rewrite). In Proceedings of VLDB 2007."},{"issue":"2","key":"e_1_3_3_90_2","article-title":"The VoltDB main memory DBMS","volume":"36","author":"Stonebraker M.","year":"2013","unstructured":"M. Stonebraker and A. Weisberg. 2013. The VoltDB main memory DBMS. IEEE Data Engineering Bulletin 36, 2 (2013), 21\u201327.","journal-title":"IEEE Data Engineering Bulletin"},{"key":"e_1_3_3_91_2","volume-title":"Proceedings of SIGMOD 2020","author":"Taft R.","year":"2020","unstructured":"R. Taft, I. Sharif, A. Matei, N. VanBenschoten, J. Lewis, T. Grieger, K. Niemi, et\u00a0al. 2020. CockroachDB: The resilient geo-distributed SQL database. In Proceedings of SIGMOD 2020. ACM, New York, NY."},{"key":"e_1_3_3_92_2","volume-title":"Proceedings of SOSP 2015","author":"Teixeira C. H. C.","year":"2015","unstructured":"C. H. C. Teixeira, A. J. Fonseca, M. Serafini, G. Siganos, M. J. Zaki, and A. Aboulnaga. 2015. Arabesque: A system for distributed graph mining. In Proceedings of SOSP 2015. ACM, New York, NY."},{"key":"e_1_3_3_93_2","volume-title":"Proceedings of SIGMOD 2012","author":"Thomson A.","year":"2012","unstructured":"A. Thomson, T. Diamond, S. C. Weng, K. Ren, P. Shao, and D. J. Abadi. 2012. Calvin: Fast distributed transactions for partitioned database systems. In Proceedings of SIGMOD 2012. ACM, New York, NY."},{"issue":"6","key":"e_1_3_3_94_2","article-title":"A survey of state management in big data processing systems","volume":"27","author":"To Q.-C.","year":"2018","unstructured":"Q.-C. To, J. Soto, and V. Markl. 2018. A survey of state management in big data processing systems. VLDB Journal 27, 6 (2018), 847\u2013872.","journal-title":"VLDB Journal"},{"key":"e_1_3_3_95_2","volume-title":"Proceedings of SIGMOD 2014","author":"Toshniwal A.","year":"2014","unstructured":"A. Toshniwal, S. Taneja, A. Shukla, K. Ramasamy, J. M. Patel, S. Kulkarni, J. Jackson, et\u00a0al. 2014. Storm@Twitter. In Proceedings of SIGMOD 2014. ACM, New York, NY."},{"key":"e_1_3_3_96_2","volume-title":"Proceedings of SIGMOD 2017","author":"Verbitski A.","year":"2017","unstructured":"A. Verbitski, A. Gupta, D. Saha, M. Brahmadesam, K. Gupta, R. Mittal, S. Krishnamurthy, S. Maurice, T. Kharatishvili, and X. Bao. 2017. Amazon Aurora: Design considerations for high throughput cloud-native relational databases. In Proceedings of SIGMOD 2017. ACM, New York, NY."},{"key":"e_1_3_3_97_2","volume-title":"Proceedings of ATC 2020","author":"Visheratin A.","year":"2020","unstructured":"A. Visheratin, A. Struckov, S. Yufa, A. Muratov, D. Nasonov, N. Butakov, Y. Kuznetsov, and M. May. 2020. Peregreen\u2014Modular database for efficient storage of historical time series in cloud environments. In Proceedings of ATC 2020."},{"key":"e_1_3_3_98_2","volume-title":"Proceedings of EuroSys 2010","author":"Zaharia M.","year":"2010","unstructured":"M. Zaharia, D. Borthakur, J. Sen Sarma, K. Elmeleegy, S. Shenker, and I. Stoica. 2010. Delay scheduling: A simple technique for achieving locality and fairness in cluster scheduling. In Proceedings of EuroSys 2010. ACM, New York, NY."},{"key":"e_1_3_3_99_2","volume-title":"Proceedings of SOSP 2013","author":"Zaharia M.","year":"2013","unstructured":"M. Zaharia, T. Das, H. Li, T. Hunter, S. Shenker, and I. Stoica. 2013. Discretized streams: Fault-tolerant streaming computation at scale. In Proceedings of SOSP 2013. ACM, New York, NY."},{"issue":"11","key":"e_1_3_3_100_2","doi-asserted-by":"crossref","DOI":"10.1145\/2934664","article-title":"Apache Spark: A unified engine for big data processing","volume":"59","author":"Zaharia M.","year":"2016","unstructured":"M. Zaharia, R. S. Xin, P. Wendell, T. Das, M. Armbrust, A. Dave, X. Meng, et\u00a0al. 2016. Apache Spark: A unified engine for big data processing. Communications of the ACM 59, 11 (2016), 56\u201365.","journal-title":"Communications of the ACM"},{"key":"e_1_3_3_101_2","volume-title":"Proceedings of SIGMOD 2021","author":"Zhou J.","year":"2021","unstructured":"J. Zhou, M. Xu, A. Shraer, B. Namasivayam, A. Miller, E. Tschannen, S. Atherton, A. J. Beamon, R. Sears, and J. Leach. 2021. FoundationDB: A distributed unbundled transactional key value store. In Proceedings of SIGMOD 2021. ACM, New York, NY."},{"issue":"2","key":"e_1_3_3_102_2","article-title":"Solar: Toward a shared-everything database on distributed log-structured storage","volume":"15","author":"Zhu T.","year":"2019","unstructured":"T. Zhu, Z. Zhao, F. Li, W. Qian, A. Zhou, D. Xie, R. Stutsman, H. Li, and H. Hu. 2019. Solar: Toward a shared-everything database on distributed log-structured storage. ACM Transactions on Storage 15, 2 (2019), Article 11, 26 pages.","journal-title":"ACM Transactions on Storage"},{"key":"e_1_3_3_103_2","first-page":"685","volume-title":"Proceedings of SIGMOD 2022","author":"Ziegler Tobias","year":"2022","unstructured":"Tobias Ziegler, Carsten Binnig, and Viktor Leis. 2022. ScaleStore: A fast and cost-efficient storage engine using DRAM, NVMe, and RDMA. In Proceedings of SIGMOD 2022. ACM, New York, NY, 685\u2013699."}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3604801","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,26]],"date-time":"2023-08-26T12:21:40Z","timestamp":1693052500000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604801"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,26]]},"references-count":102,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1,31]]}},"alternative-id":["10.1145\/3604801"],"URL":"https:\/\/doi.org\/10.1145\/3604801","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,26]]},"assertion":[{"value":"2022-03-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-31","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-26","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}