{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:51:19Z","timestamp":1783439479575,"version":"3.54.6"},"reference-count":25,"publisher":"Association for Computing Machinery (ACM)","license":[{"start":{"date-parts":[[2022,3,4]],"date-time":"2022-03-04T00:00:00Z","timestamp":1646352000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ACM J. Exp. Algorithmics"],"published-print":{"date-parts":[[2022,12,31]]},"abstract":"<jats:p>\n            Bloom and cuckoo filters provide fast approximate set membership while using little memory. Engineers use them to avoid expensive disk and network accesses. The recently introduced xor filters can be faster and smaller than Bloom and cuckoo filters. The xor filters are within 23% of the theoretical lower bound in storage as opposed to 44% for Bloom filters. Inspired by Dietzfelbinger and Walzer, we build probabilistic filters\u2014called\n            <jats:italic>binary fuse filters<\/jats:italic>\n            \u2014that are within 13% of the storage lower bound\u2014without sacrificing query speed. As an additional benefit, the construction of the new binary fuse filters can be more than twice as fast as the construction of xor filters. By slightly sacrificing query speed, we further reduce storage to within 8% of the lower bound. We compare the performance against a wide range of competitive alternatives such as Bloom filters, blocked Bloom filters, vector quotient filters, cuckoo filters, and the recent ribbon filters. Our experiments suggest that binary fuse filters are superior to xor filters.\n          <\/jats:p>","DOI":"10.1145\/3510449","type":"journal-article","created":{"date-parts":[[2022,3,4]],"date-time":"2022-03-04T10:43:30Z","timestamp":1646390610000},"page":"1-15","source":"Crossref","is-referenced-by-count":23,"title":["Binary Fuse Filters: Fast and Smaller Than Xor Filters"],"prefix":"10.1145","volume":"27","author":[{"given":"Thomas Mueller","family":"Graf","sequence":"first","affiliation":[{"name":"University of Quebec (TELUQ), Montreal, Quebec, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3306-6922","authenticated-orcid":false,"given":"Daniel","family":"Lemire","sequence":"additional","affiliation":[{"name":"University of Quebec (TELUQ), Montreal, Quebec, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,3,4]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/362686.362692"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.5555\/2394893.2394911"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.14778\/3213880.3213884"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/0022-0000(79)90044-8"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-87744-8_22"},{"key":"e_1_3_3_7_2","first-page":"30","volume-title":"Proceedings of the 15th Annual ACM-SIAM Symposium on Discrete Algorithms","author":"Chazelle Bernard","year":"2004","unstructured":"Bernard Chazelle, Joe Kilian, Ronitt Rubinfeld, and Ayellet Tal. 2004. The bloomier filter: An efficient data structure for static support lookup tables. In Proceedings of the 15th Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 30\u201339."},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-70575-8_32"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.4230\/LIPIcs.ESA.2019.38"},{"key":"e_1_3_3_10_2","article-title":"Ribbon filter: practically smaller than Bloom and Xor","author":"Dillinger Peter","year":"2021","unstructured":"Peter Dillinger and Stefan Walzer. 2021. Ribbon filter: practically smaller than Bloom and Xor. Retrieved January 27, 2022 from https:\/\/arxiv.org\/abs\/2103.02515. (last checked July 2021).","journal-title":"https:\/\/arxiv.org\/abs\/2103.02515. (last checked July 2021)"},{"key":"e_1_3_3_11_2","article-title":"Cuckoo Filter","author":"Fan Bin","year":"2013","unstructured":"Bin Fan and David G. Andersen. 2013\u20132017. Cuckoo Filter. Retrieved January 27, 2022 from https:\/\/github.com\/efficient\/cuckoofilter, commit: aac6569cf30f0dfcf39edec1799fc3f8d6f594da.","journal-title":"https:\/\/github.com\/efficient\/cuckoofilter, commit: aac6569cf30f0dfcf39edec1799fc3f8d6f594da"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/2674005.2674994"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-38851-9_23"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3376122"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2461"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.14778\/3303753.3303757"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.14778\/3303753.3303757"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2021.e07442"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/2592798.2592820"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2010.81"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3035963"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3452841"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/2619228.2619234"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3376122"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/MELCON.2010.5476244"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611976465.131"}],"container-title":["ACM Journal of Experimental Algorithmics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3510449","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3510449","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:46Z","timestamp":1750183786000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3510449"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,4]]},"references-count":25,"alternative-id":["10.1145\/3510449"],"URL":"https:\/\/doi.org\/10.1145\/3510449","relation":{},"ISSN":["1084-6654","1084-6654"],"issn-type":[{"value":"1084-6654","type":"print"},{"value":"1084-6654","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,4]]}}}