{"id":"https://openalex.org/W3146448298","doi":"https://doi.org/10.1145/3448016.3457552","title":"Real-time Data Infrastructure at Uber","display_name":"Real-time Data Infrastructure at Uber","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3146448298","doi":"https://doi.org/10.1145/3448016.3457552","mag":"3146448298"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3457552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448016.3457552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.00087","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yupeng Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yupeng Fu","raw_affiliation_strings":["Uber, Inc., San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Uber, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I2946016260"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chinmay Soman","orcid":null},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chinmay Soman","raw_affiliation_strings":["Uber, Inc., San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Uber, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I2946016260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2946016260"],"apc_list":null,"apc_paid":null,"fwci":7.3802,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.9711261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2503","last_page":"2516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10772","display_name":"Distributed systems and fault tolerance","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6952000260353088},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.6657000184059143},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6516000032424927},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.6287000179290771},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4803999960422516},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3831000030040741},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.3630000054836273}],"concepts":[{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6952000260353088},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.6657000184059143},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6516000032424927},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.6287000179290771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5537999868392944},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5449000000953674},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.32829999923706055},{"id":"https://openalex.org/C165609540","wikidata":"https://www.wikidata.org/wiki/Q1172486","display_name":"Data breach","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29030001163482666},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2831000089645386},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2793999910354614},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.2678999900817871},{"id":"https://openalex.org/C121017731","wikidata":"https://www.wikidata.org/wiki/Q11661","display_name":"Information technology","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.26089999079704285},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C91262260","wikidata":"https://www.wikidata.org/wiki/Q528074","display_name":"End user","level":2,"score":0.25699999928474426}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3448016.3457552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448016.3457552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2104.00087","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.00087","pdf_url":"https://arxiv.org/pdf/2104.00087","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2104.00087","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.00087","pdf_url":"https://arxiv.org/pdf/2104.00087","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1969877208","https://openalex.org/W1976821017","https://openalex.org/W2008503861","https://openalex.org/W2038412523","https://openalex.org/W2054584570","https://openalex.org/W2057714068","https://openalex.org/W2102729946","https://openalex.org/W2114226753","https://openalex.org/W2173213060","https://openalex.org/W2244876453","https://openalex.org/W2247317079","https://openalex.org/W2437053200","https://openalex.org/W2476844261","https://openalex.org/W2487598231","https://openalex.org/W2612041618","https://openalex.org/W2798611317","https://openalex.org/W2949762319","https://openalex.org/W2951386311","https://openalex.org/W2967032974","https://openalex.org/W3034485723","https://openalex.org/W3085441975","https://openalex.org/W3085924233","https://openalex.org/W3085940077","https://openalex.org/W3086896769","https://openalex.org/W3137759927"],"related_works":[],"abstract_inverted_index":{"Uber's":[0,156,164],"business":[1],"is":[2,10,30,66],"highly":[3],"real-time":[4,101,179],"in":[5,45,118,155],"nature.":[6],"PBs":[7],"of":[8,33,50,99,134,139],"data":[9,80,102],"continuously":[11,113],"being":[12],"collected":[13],"from":[14],"the":[15,89,96,100,119,131,135,151,160,187],"end":[16],"users":[17],"such":[18,53],"as":[19,54,191],"Uber":[20],"drivers,":[21],"riders,":[22],"restaurants,":[23],"eaters":[24],"and":[25,39,83,104,147,158,167,176,181,195],"so":[26],"on":[27,126,186],"everyday.":[28],"There":[29],"a":[31,48],"lot":[32],"valuable":[34],"information":[35],"to":[36,70,74,88,112,149,162],"be":[37,43],"processed":[38],"many":[40],"decisions":[41],"must":[42],"made":[44],"seconds":[46],"for":[47,115,130],"variety":[49],"use":[51,174],"cases":[52,175],"customer":[55],"incentives,":[56],"fraud":[57],"detection,":[58],"machine":[59],"learning":[60],"model":[61],"prediction.":[62],"In":[63,91],"addition,":[64],"there":[65],"an":[67],"increasing":[68],"need":[69,111],"expose":[71],"this":[72,92],"ability":[73],"different":[75],"user":[76],"categories,":[77],"including":[78],"engineers,":[79],"scientists,":[81],"executives":[82],"operations":[84],"personnel":[85],"which":[86],"adds":[87],"complexity.":[90],"paper,":[93],"we":[94,110,123,143,184,189,192],"present":[95],"overall":[97],"architecture":[98],"infrastructure":[103],"identify":[105],"three":[106],"scaling":[107],"challenges":[108],"that":[109],"address":[114],"each":[116],"component":[117],"architecture.":[120],"At":[121],"Uber,":[122],"heavily":[124],"rely":[125],"open":[127],"source":[128],"technologies":[129],"key":[132],"areas":[133],"infrastructure.":[136],"On":[137],"top":[138],"those":[140],"open-source":[141,152],"software,":[142],"add":[144],"significant":[145],"improvements":[146],"customizations":[148],"make":[150],"solutions":[153,180],"fit":[154],"environment":[157],"bridge":[159],"gaps":[161],"meet":[163],"unique":[165],"scale":[166],"requirements.":[168],"We":[169],"then":[170],"highlight":[171],"several":[172],"important":[173],"show":[177],"their":[178],"tradeoffs.":[182],"Finally,":[183],"reflect":[185],"lessons":[188],"learned":[190],"built,":[193],"operated":[194],"scaled":[196],"these":[197],"systems.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-04-13T00:00:00"}