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Other systems run graph analytics workloads efficiently, but cannot properly support transactions.<\/jats:p>\n          <jats:p>This paper presents LiveGraph, a graph storage system that outperforms both the best graph transactional systems and the best solutions for real-time graph analytics on fresh data. LiveGraph achieves this by ensuring that adjacency list scans, a key operation in graph workloads, are purely sequential: they never require random accesses even in presence of concurrent transactions. Such pure-sequential operations are enabled by combining a novel graph-aware data structure, the Transactional Edge Log (TEL), with a concurrency control mechanism that leverages TEL's data layout. Our evaluation shows that LiveGraph significantly outperforms state-of-the-art (graph) database solutions on both transactional and real-time analytical workloads.<\/jats:p>","DOI":"10.14778\/3384345.3384351","type":"journal-article","created":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T14:21:06Z","timestamp":1585232466000},"page":"1020-1034","source":"Crossref","is-referenced-by-count":60,"title":["LiveGraph"],"prefix":"10.14778","volume":"13","author":[{"given":"Xiaowei","family":"Zhu","sequence":"first","affiliation":[{"name":"Tsinghua University"}]},{"given":"Guanyu","family":"Feng","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Marco","family":"Serafini","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst"}]},{"given":"Xiaosong","family":"Ma","sequence":"additional","affiliation":[{"name":"Qatar Computing Research Institute"}]},{"given":"Jiping","family":"Yu","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Lei","family":"Xie","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Ashraf","family":"Aboulnaga","sequence":"additional","affiliation":[{"name":"Qatar Computing Research Institute"}]},{"given":"Wenguang","family":"Chen","sequence":"additional","affiliation":[{"name":"Tsinghua University and Beijing National Research Center for Information Science and Technology"}]}],"member":"320","published-online":{"date-parts":[[2020,3,26]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"https:\/\/www.gartner.com\/en\/newsroom\/press-rele ases\/2019-02-18-gartner-identifies-top-10-data -and-analytics-technolo.  https:\/\/www.gartner.com\/en\/newsroom\/press-rele ases\/2019-02-18-gartner-identifies-top-10-data -and-analytics-technolo."},{"key":"e_1_2_1_2_1","unstructured":"http:\/\/rocksdb.org\/.  http:\/\/rocksdb.org\/."},{"key":"e_1_2_1_3_1","unstructured":"https:\/\/neo4j.com\/.  https:\/\/neo4j.com\/."},{"key":"e_1_2_1_4_1","unstructured":"https:\/\/symas.com\/lmdb\/.  https:\/\/symas.com\/lmdb\/."},{"key":"e_1_2_1_5_1","unstructured":"https:\/\/www.postgresql.org\/.  https:\/\/www.postgresql.org\/."},{"key":"e_1_2_1_6_1","unstructured":"https:\/\/virtuoso.openlinksw.com\/.  https:\/\/virtuoso.openlinksw.com\/."},{"key":"e_1_2_1_7_1","unstructured":"https: \/\/github.com\/ldbc\/ldbc snb implementations.  https: \/\/github.com\/ldbc\/ldbc snb implementations."},{"key":"e_1_2_1_8_1","unstructured":"https:\/\/en.wikipedia.org\/wiki\/Database index#C lustered.  https:\/\/en.wikipedia.org\/wiki\/Database index#C lustered."},{"key":"e_1_2_1_9_1","unstructured":"http:\/\/titan.thinkaurelius.com\/.  http:\/\/titan.thinkaurelius.com\/."},{"key":"e_1_2_1_10_1","unstructured":"http:\/\/orientdb.com\/.  http:\/\/orientdb.com\/."},{"key":"e_1_2_1_11_1","unstructured":"https:\/\/www.arangodb.com\/.  https:\/\/www.arangodb.com\/."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465296"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2749441"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.14778\/3025111.3025116"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732232.2732237"},{"key":"e_1_2_1_16_1","first-page":"1","volume-title":"ACM SIGMOD Record","author":"Berenson H.","year":"1995","unstructured":"H. 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