{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T17:02:59Z","timestamp":1757610179886,"version":"3.44.0"},"reference-count":76,"publisher":"Association for Computing Machinery (ACM)","issue":"8","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:p>\n            Many modern applications require real-time analytics, where analytical processing (AP) workloads needs access to the latest data updates from a transactional processing (TP) engine. However, managing separate TP and AP engines across teams complicates achieving real-time analytics without switching to specialized HTAP systems. To address this challenge, we introduce\n            <jats:italic toggle=\"yes\">off-the-shelf real-time analytics<\/jats:italic>\n            , a system design that leverages the existing TP and AP engines to provide (1) the latest transactional updates for analytical queries and (2) support for efficient\n            <jats:italic toggle=\"yes\">transactional<\/jats:italic>\n            analytics-transactions that combine transactional logic and analytical queries within a single ACID transaction-at various isolation levels. We demonstrate this concept with a new service called\n            <jats:italic toggle=\"yes\">Hermes<\/jats:italic>\n            , which acts as a middleware that merges log records with analytical reads without altering existing engines. Our evaluation utilizes two AP engines,\n            <jats:italic toggle=\"yes\">FlexPushdownDB<\/jats:italic>\n            and\n            <jats:italic toggle=\"yes\">DuckDB<\/jats:italic>\n            , with\n            <jats:italic toggle=\"yes\">MySQL<\/jats:italic>\n            as the TP engine. Using the\n            <jats:italic toggle=\"yes\">HATtrick<\/jats:italic>\n            benchmark and a new workload called\n            <jats:italic toggle=\"yes\">Transactional Analytics Workload<\/jats:italic>\n            (TAW), we compare Hermes with the leading HTAP solution,\n            <jats:italic toggle=\"yes\">TiDB.<\/jats:italic>\n            Our results indicate that Hermes performs comparably to current HTAP solutions for real-time analytics and surpasses them by 3\u00d7 in transactional analytics performance.\n          <\/jats:p>","DOI":"10.14778\/3742728.3742731","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T13:32:53Z","timestamp":1756906373000},"page":"2334-2347","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Hermes: Off-the-Shelf Real-Time Transactional Analytics"],"prefix":"10.14778","volume":"18","author":[{"given":"Elena","family":"Milkai","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison"}]},{"given":"Xiangyao","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison"}]},{"given":"Jignesh M.","family":"Patel","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}]}],"member":"320","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2024. 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