{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T08:22:39Z","timestamp":1769156559756,"version":"3.49.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T00:00:00Z","timestamp":1662508800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T00:00:00Z","timestamp":1662508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162050"],"award-info":[{"award-number":["62162050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162050"],"award-info":[{"award-number":["62162050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162050"],"award-info":[{"award-number":["62162050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62162050"],"award-info":[{"award-number":["62162050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cloud Comp"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Cloud-native database systems have started to gain broad support and popularity due to more and more applications and systems moving to the cloud. Various cloud-native databases have been emerging in recent years, but their developments are still in the primary stage. At this stage, database developers are generally confused about improving the performance of the database by applying AI technologies. The maturity model can help database developers formulate the measures and clarify the improvement path during development. However, the current maturity models are unsuitable for cloud-native databases since their architecture and resource management differ from traditional databases. Hence, we propose a maturity model for AI-empowered cloud-native databases from the perspective of resource management. We employ a systematic literature review and expert interviews to conduct the maturity model. Also, we develop an assessment tool based on the maturity model to help developers assess cloud-native databases. And we provide an assessment case to prove our maturity model. The assessment case results show that the database\u2019s development direction conforms to the maturity model. It proves the effectiveness of the maturity model.<\/jats:p>","DOI":"10.1186\/s13677-022-00318-1","type":"journal-article","created":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T11:05:30Z","timestamp":1662548730000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A maturity model for AI-empowered cloud-native databases: from the perspective of resource management"],"prefix":"10.1186","volume":"11","author":[{"given":"Xiaoyue","family":"Feng","sequence":"first","affiliation":[]},{"given":"Chaopeng","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Tianzhe","family":"Jiao","sequence":"additional","affiliation":[]},{"given":"Jie","family":"Song","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"issue":"12","key":"318_CR1","doi-asserted-by":"publisher","first-page":"2263","DOI":"10.14778\/3352063.3352141","volume":"12","author":"F Li","year":"2019","unstructured":"Li F (2019) Cloud-native database systems at Alibaba: opportunities and challenges. Proc VLDB Endowment 12(12):2263\u20132272","journal-title":"Proc VLDB Endowment"},{"issue":"1","key":"318_CR2","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s10619-018-7252-2","volume":"37","author":"DH Ton That","year":"2019","unstructured":"Ton That DH, Wagner J, Rasin A, Malik T (2019) PLI+: efficient clustering of cloud databases. Distributed Parallel Databases 37(1):177\u2013208","journal-title":"Distributed Parallel Databases"},{"key":"318_CR3","unstructured":"GB\/T 33136\u20132016 Information technology service\u2014Service capability maturity model of data center. Available at: https:\/\/openstd.samr.gov.cn\/bzgk\/gb\/newGbInfo?hcno=F7A2242CAA62FD4466E8BAB0F92661D8. Accessed 20 June 2022"},{"issue":"12","key":"318_CR4","doi-asserted-by":"publisher","first-page":"2059","DOI":"10.14778\/3352063.3352124","volume":"12","author":"C Zhan","year":"2019","unstructured":"Zhan C, Su M, Wei C et al (2019) AnalyticDB: real-time OLAP database system at alibaba cloud. Proc VLDB Endowment 12(12):2059\u20132070","journal-title":"Proc VLDB Endowment"},{"key":"318_CR5","doi-asserted-by":"publisher","first-page":"1743","DOI":"10.1145\/3299869.3314047","volume-title":"Proceedings of the 2019 International Conference on Management of Data","author":"P Antonopoulos","year":"2019","unstructured":"Antonopoulos P, Budovski A, Diaconu C et al (2019) Socrates: the new sql server in the cloud. In: Proceedings of the 2019 International Conference on Management of Data, pp 1743\u20131756"},{"key":"318_CR6","doi-asserted-by":"publisher","first-page":"2570","DOI":"10.1145\/3448016.3457553","volume-title":"Proceedings of the 2021 International Conference on Management of Data","author":"Z Pang","year":"2021","unstructured":"Pang Z, Lu Q, Chen S et al (2021) ArkDB: a key-value engine for scalable cloud storage services. In: Proceedings of the 2021 International Conference on Management of Data, pp 2570\u20132583"},{"key":"318_CR7","doi-asserted-by":"publisher","unstructured":"Chen Y, Zhao F, Lu Y, Chen X (2021) Dynamic task offloading for mobile edge computing with hybrid energy supply. Tsinghua Sci Technol. https:\/\/doi.org\/10.26599\/TST.2021.9010050","DOI":"10.26599\/TST.2021.9010050"},{"key":"318_CR8","doi-asserted-by":"crossref","unstructured":"Xu J, Li D, Gu W, Chen Y (2022) UAV-assisted task offloading for IoT in smart buildings and environment via deep reinforcement learning. Build Environ 222:109218","DOI":"10.1016\/j.buildenv.2022.109218"},{"issue":"5","key":"318_CR9","doi-asserted-by":"publisher","first-page":"4584","DOI":"10.1109\/TVT.2021.3133586","volume":"71","author":"Y Chen","year":"2021","unstructured":"Chen Y, Zhao F, Chen X, Wu Y (2021) Efficient multi-vehicle task offloading for mobile edge computing in 6G networks. IEEE Trans Veh Technol 71(5):4584\u20134596","journal-title":"IEEE Trans Veh Technol"},{"key":"318_CR10","doi-asserted-by":"crossref","unstructured":"Xu X, Jiang Q, Zhang P, Cao X et al (2022) Game theory for distributed IoV task offloading with fuzzy neural network in edge computing. IEEE Trans Fuzzy Syst","DOI":"10.1109\/TFUZZ.2022.3158000"},{"key":"318_CR11","doi-asserted-by":"crossref","unstructured":"Chen Y, Gu W, Li K (2022) Dynamic task offloading for internet of things in mobile edge computing via deep reinforcement learning. Int J Commun Syst 2022:e5154","DOI":"10.1002\/dac.5154"},{"key":"318_CR12","doi-asserted-by":"crossref","unstructured":"Huang J, Tong Z, Feng Z (2022) Geographical POI recommendation for internet of things: a federated learning approach using matrix factorization. Int J Commun Syst 2022:e5161","DOI":"10.1002\/dac.5161"},{"key":"318_CR13","doi-asserted-by":"crossref","unstructured":"Xu X, Tian H, Zhang X, Qi L, He Q, Dou W (2022) DisCOV: distributed COVID-19 detection on X-ray images with edge-cloud collaboration. IEEE Trans Serv Comput 15(3):1206\u20131219","DOI":"10.1109\/TSC.2022.3142265"},{"issue":"1","key":"318_CR14","doi-asserted-by":"publisher","first-page":"32","DOI":"10.26599\/BDMA.2021.9020016","volume":"5","author":"AK Sandhu","year":"2021","unstructured":"Sandhu AK (2021) Big data with cloud computing: discussions and challenges. Big Data Mining Analytics 5(1):32\u201340","journal-title":"Big Data Mining Analytics"},{"issue":"1","key":"318_CR15","doi-asserted-by":"publisher","first-page":"37","DOI":"10.23919\/ICN.2020.0002","volume":"1","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Zhang H, Cosmas J, Jawad N et al (2020) Internet of radio and light: 5G building network radio and edge architecture. Intell Converged Netw 1(1):37\u201357","journal-title":"Intell Converged Netw"},{"issue":"8","key":"318_CR16","doi-asserted-by":"publisher","first-page":"1468","DOI":"10.1108\/IMDS-12-2015-0495","volume":"116","author":"M Comuzzi","year":"2016","unstructured":"Comuzzi M, Patel A (2016) How organisations leverage big data: a maturity model. Ind Manag Data Syst 116(8):1468\u20131492","journal-title":"Ind Manag Data Syst"},{"issue":"1","key":"318_CR17","first-page":"57","volume":"47","author":"GAI Guoqiang","year":"2021","unstructured":"Guoqiang GAI, Tingkun Y, Jun XIE, Chenning HUANG (2021) Database service ecology and system in China. Inform Commun Technol Policy 47(1):57\u201362","journal-title":"Inform Commun Technol Policy"},{"key":"318_CR18","first-page":"19","volume-title":"8th International Conference on Cloud Computing and Services Science (CLOSER)","author":"J Spillner","year":"2018","unstructured":"Spillner J, Bogado Y, Ben\u00edtez W, L\u00f3pez Pires F (2018) Co-transformation to cloud-native applications: development experiences and experimental evaluation. In: 8th International Conference on Cloud Computing and Services Science (CLOSER). SciTePress, Funchal, pp 19\u201321"},{"issue":"3","key":"318_CR19","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1108\/JEIM-10-2020-0397","volume":"35","author":"W Chen","year":"2021","unstructured":"Chen W, Liu C, Xing F, Peng G, Yang X (2021) Establishment of a maturity model to assess the development of industrial AI in smart manufacturing. J Enterp Inf Manag 35(3):701\u2013728","journal-title":"J Enterp Inf Manag"},{"key":"318_CR20","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.infsof.2016.01.010","volume":"75","author":"A Tarhan","year":"2016","unstructured":"Tarhan A, Turetken O, Reijers HA (2016) Business process maturity models: a systematic literature review. Inf Softw Technol 75:122\u2013134","journal-title":"Inf Softw Technol"},{"key":"318_CR21","doi-asserted-by":"publisher","first-page":"e661","DOI":"10.7717\/peerj-cs.661","volume":"7","author":"RB Sadiq","year":"2021","unstructured":"Sadiq RB, Safie N, Abd Rahman AH et al (2021) Artificial intelligence maturity model: a systematic literature review. PeerJ Comput Sci 7:e661","journal-title":"PeerJ Comput Sci"},{"key":"318_CR22","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/978-3-030-58666-9_21","volume-title":"International conference on business process management","author":"V Felch","year":"2020","unstructured":"Felch V, Asdecker B (2020) Quo Vadis, business process maturity model? Learning from the past to envision the future. In: International conference on business process management. Springer, Cham, pp 368\u2013383"},{"issue":"1","key":"318_CR23","doi-asserted-by":"publisher","first-page":"103569","DOI":"10.1016\/j.im.2021.103569","volume":"59","author":"A Dutta","year":"2022","unstructured":"Dutta A, Roy R, Seetharaman P (2022) An assimilation maturity model for IT governance and auditing. Inf Manag 59(1):103569","journal-title":"Inf Manag"},{"issue":"6","key":"318_CR24","doi-asserted-by":"publisher","first-page":"4159","DOI":"10.1109\/TII.2020.3012157","volume":"17","author":"L Qi","year":"2020","unstructured":"Qi L, Hu C, Zhang X, Khosravi MR, Sharma S, Pang S, Wang T (2020) Privacy-aware data fusion and prediction with spatial-temporal context for smart city industrial environment. IEEE Transact Industr Inform 17(6):4159\u20134167","journal-title":"IEEE Transact Industr Inform"},{"issue":"1","key":"318_CR25","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1057\/ejis.2011.51","volume":"22","author":"JF Wolfswinkel","year":"2013","unstructured":"Wolfswinkel JF, Furtmueller E, Wilderom CP (2013) Using grounded theory as a method for rigorously reviewing literature. Eur J Inf Syst 22(1):45\u201355","journal-title":"Eur J Inf Syst"},{"key":"318_CR26","doi-asserted-by":"publisher","DOI":"10.1201\/b19467","volume-title":"Evidence-based software engineering and systematic reviews","author":"BA Kitchenham","year":"2015","unstructured":"Kitchenham BA, Budgen D, Brereton P (2015) Evidence-based software engineering and systematic reviews. CRC Press, Boca Raton"},{"key":"318_CR27","doi-asserted-by":"crossref","unstructured":"Chen Y, Xing H, Ma Z, Chen X, Huang J (2022) Cost-efficient edge caching for NOMA-enabled IoT services. Chin Commun","DOI":"10.1155\/2022\/8072493"},{"issue":"3","key":"318_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2491245","volume":"31","author":"JC Corbett","year":"2013","unstructured":"Corbett JC, Dean J, Epstein M et al (2013) Spanner: Google\u2019s globally distributed database. ACM Transact Comput Syst (TOCS) 31(3):1\u201322","journal-title":"ACM Transact Comput Syst (TOCS)"},{"issue":"12","key":"318_CR29","doi-asserted-by":"publisher","first-page":"3072","DOI":"10.14778\/3415478.3415535","volume":"13","author":"D Huang","year":"2020","unstructured":"Huang D, Liu Q, Cui Q et al (2020) TiDB: a raft-based HTAP database. Proc VLDB Endowment 13(12):3072\u20133084","journal-title":"Proc VLDB Endowment"},{"key":"318_CR30","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1145\/3035918.3056101","volume-title":"Proceedings of the 2017 ACM International Conference on Management of Data","author":"A Verbitski","year":"2017","unstructured":"Verbitski A, Gupta A, Saha D et al (2017) Amazon aurora: design considerations for high throughput cloud-native relational databases. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp 1041\u20131052"},{"key":"318_CR31","first-page":"29","volume-title":"18th USENIX conference on file and storage technologies (FAST 20)","author":"W Cao","year":"2020","unstructured":"Cao W, Liu Y, Cheng Z et al (2020) POLARDB meets computational storage: efficiently support analytical workloads in cloud-native relational database. In: 18th USENIX conference on file and storage technologies (FAST 20), pp 29\u201341"},{"issue":"12","key":"318_CR32","doi-asserted-by":"publisher","first-page":"1849","DOI":"10.14778\/3229863.3229872","volume":"11","author":"W Cao","year":"2018","unstructured":"Cao W, Liu Z, Wang P et al (2018) PolarFS: an ultra-low latency and failure resilient distributed file system for shared storage cloud database. Proc VLDB Endowment 11(12):1849\u20131862","journal-title":"Proc VLDB Endowment"},{"key":"318_CR33","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.1145\/3318464.3386129","volume-title":"Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data","author":"A Depoutovitch","year":"2020","unstructured":"Depoutovitch A, Chen C, Chen J et al (2020) Taurus database: how to be fast, available, and frugal in the cloud. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp 1463\u20131478"},{"issue":"2","key":"318_CR34","doi-asserted-by":"publisher","first-page":"1964","DOI":"10.1109\/TVT.2021.3133696","volume":"71","author":"J Huang","year":"2021","unstructured":"Huang J, Lv B, Wu Y, Chen Y, Shen X (2021) Dynamic admission control and resource allocation for mobile edge computing enabled small cell network. IEEE Trans Veh Technol 71(2):1964\u20131973","journal-title":"IEEE Trans Veh Technol"},{"issue":"7","key":"318_CR35","doi-asserted-by":"publisher","first-page":"4925","DOI":"10.1109\/TII.2020.3028963","volume":"17","author":"Y Chen","year":"2020","unstructured":"Chen Y, Liu Z, Zhang Y, Wu Y, Chen X, Zhao L (2020) Deep reinforcement learning-based dynamic resource management for mobile edge computing in industrial internet of things. IEEE Transact Industr Inform 17(7):4925\u20134934","journal-title":"IEEE Transact Industr Inform"},{"issue":"2","key":"318_CR36","doi-asserted-by":"publisher","first-page":"181","DOI":"10.23919\/ICN.2020.0014","volume":"1","author":"S Nath","year":"2020","unstructured":"Nath S, Wu J (2020) Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems. Intell Converged Netw 1(2):181\u2013198","journal-title":"Intell Converged Netw"},{"key":"318_CR37","unstructured":"Herodotou H, Lim H, Luo G et al (2011) Starfish: a self-tuning system for big data analytics. 5th Biennial Conf Innovative Data Syst Res (CIDR'11) 11(2011):261\u2013272. Asilomar"},{"key":"318_CR38","doi-asserted-by":"crossref","unstructured":"Li L, Gruenwald L (2016) An SLA and operation cost aware performance re-tuning algorithm for cloud databases. 2016 IEEE 9th Int Conf Cloud Comput (CLOUD) 2016:966\u2013969","DOI":"10.1109\/CLOUD.2016.0146"},{"key":"318_CR39","doi-asserted-by":"crossref","unstructured":"Wang X, Li N, Zhang L, Zhang X, Zhao Q (2021) Rapid trend prediction for large-scale cloud database KPIs by clustering. 2021 IEEE\/ACM Int Workshop Cloud Intell (CloudIntelligence) 2021:1\u20136","DOI":"10.1109\/CloudIntelligence52565.2021.00010"},{"issue":"5","key":"318_CR40","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1109\/TPDS.2014.2319095","volume":"26","author":"P Xiong","year":"2014","unstructured":"Xiong P, Chi Y, Zhu S, Moon HJ, Pu C, Hacg\u00fcm\u00fc\u015f H (2014) SmartSLA: cost-sensitive management of virtualized resources for CPU-bound database services. IEEE Transact Parallel Distribut Syst 26(5):1441\u20131451","journal-title":"IEEE Transact Parallel Distribut Syst"},{"key":"318_CR41","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1145\/2371536.2371541","volume-title":"Proceedings of the 9th international conference on Autonomic computing","author":"L Wang","year":"2012","unstructured":"Wang L, Xu J, Zhao M (2012) Application-aware cross-layer virtual machine resource management. In: Proceedings of the 9th international conference on Autonomic computing, pp 13\u201322"},{"key":"318_CR42","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1016\/j.ins.2017.07.006","volume":"433","author":"S Sotiriadis","year":"2018","unstructured":"Sotiriadis S, Bessis N, Buyya R (2018) Self managed virtual machine scheduling in cloud systems. Inf Sci 433:381\u2013400","journal-title":"Inf Sci"},{"issue":"10","key":"318_CR43","doi-asserted-by":"publisher","first-page":"1221","DOI":"10.14778\/3339490.3339503","volume":"12","author":"J Tan","year":"2019","unstructured":"Tan J, Zhang T, Li F et al (2019) iBTune: individualized buffer tuning for large-scale cloud databases. Proc VLDB Endowment 12(10):1221\u20131234","journal-title":"Proc VLDB Endowment"},{"issue":"5","key":"318_CR44","doi-asserted-by":"publisher","first-page":"1683","DOI":"10.1016\/j.compeleceng.2014.04.017","volume":"40","author":"\u00d6 Arma\u011fan","year":"2014","unstructured":"Arma\u011fan \u00d6, G\u00f6ren-S\u00fcmer L (2014) Feedback control for multi-resource usage of virtualised database server. Comput Electr Eng 40(5):1683\u20131702","journal-title":"Comput Electr Eng"},{"issue":"1","key":"318_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eij.2014.01.002","volume":"15","author":"FA Omara","year":"2014","unstructured":"Omara FA, Khattab SM, Sahal R (2014) Optimum resource allocation of database in cloud computing. Egypt Inform J 15(1):1\u201312","journal-title":"Egypt Inform J"},{"key":"318_CR46","doi-asserted-by":"publisher","first-page":"2102","DOI":"10.1145\/3448016.3457291","volume-title":"Proceedings of the 2021 International Conference on Management of Data","author":"X Zhang","year":"2021","unstructured":"Zhang X, Wu H, Chang Z et al (2021) ResTune: resource oriented tuning boosted by meta-learning for cloud databases. In: Proceedings of the 2021 International Conference on Management of Data, pp 2102\u20132114"},{"key":"318_CR47","first-page":"1","volume-title":"Proceedings of the 2nd ACM Symposium on Cloud Computing","author":"Z Shen","year":"2011","unstructured":"Shen Z, Subbiah S, Gu X, Wilkes J (2011) CloudScale: elastic resource scaling for multi-tenant cloud systems. In: Proceedings of the 2nd ACM Symposium on Cloud Computing, pp 1\u201314"},{"issue":"2","key":"318_CR48","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1093\/comjnl\/bxaa030","volume":"65","author":"Z Salmanian","year":"2022","unstructured":"Salmanian Z, Izadkhah H, Isazadeh A (2022) Auto-scale resource provisioning in IaaS clouds. Comput J 65(2):297\u2013309","journal-title":"Comput J"},{"key":"318_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jpdc.2018.04.016","volume":"120","author":"BB JV","year":"2018","unstructured":"JV BB, Dharma D (2018) HAS: hybrid auto-scaler for resource scaling in cloud environment. J Parallel Distribut Comput 120:1\u201315","journal-title":"J Parallel Distribut Comput"},{"issue":"7","key":"318_CR50","doi-asserted-by":"publisher","first-page":"726","DOI":"10.14778\/2752939.2752942","volume":"8","author":"V Narasayya","year":"2015","unstructured":"Narasayya V, Menache I, Singh M et al (2015) Sharing buffer pool memory in multi-tenant relational database-as-a-service. Proc VLDB Endowment 8(7):726\u2013737","journal-title":"Proc VLDB Endowment"},{"key":"318_CR51","doi-asserted-by":"publisher","first-page":"2477","DOI":"10.1145\/3448016.3457560","volume-title":"Proceedings of the 2021 International Conference on Management of Data","author":"W Cao","year":"2021","unstructured":"Cao W, Zhang Y, Yang X et al (2021) Polardb serverless: a cloud native database for disaggregated data centers. In: Proceedings of the 2021 International Conference on Management of Data, pp 2477\u20132489"},{"key":"318_CR52","doi-asserted-by":"publisher","first-page":"1923","DOI":"10.1145\/2882903.2903733","volume-title":"Proceedings of the 2016 International Conference on Management of Data","author":"S Das","year":"2016","unstructured":"Das S, Li F, Narasayya VR, K\u00f6nig AC (2016) Automated demand-driven resource scaling in relational database-as-a-service. In: Proceedings of the 2016 International Conference on Management of Data, pp 1923\u20131934"}],"container-title":["Journal of Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-022-00318-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13677-022-00318-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-022-00318-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T11:21:21Z","timestamp":1662549681000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofcloudcomputing.springeropen.com\/articles\/10.1186\/s13677-022-00318-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,7]]},"references-count":52,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["318"],"URL":"https:\/\/doi.org\/10.1186\/s13677-022-00318-1","relation":{},"ISSN":["2192-113X"],"issn-type":[{"value":"2192-113X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,7]]},"assertion":[{"value":"15 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"39"}}