{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T05:55:21Z","timestamp":1781330121529,"version":"3.54.1"},"reference-count":70,"publisher":"Association for Computing Machinery (ACM)","issue":"6","funder":[{"name":"National Research Foundation of Korea (NRF) grant funded by the Korean government","award":["2022R1A2C2008427"],"award-info":[{"award-number":["2022R1A2C2008427"]}]},{"name":"SK hynix Inc."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Manag. Data"],"published-print":{"date-parts":[[2025,12,4]]},"abstract":"<jats:p>\n                    HTAP systems aim to unify operational and analytical workloads, yet real-time analytics remains constrained by the overhead of extract-transform-load (ETL) operations. Existing solutions often rely on dual-system architectures, incurring substantial resource costs and delays from data reformatting and relocation. We present\n                    <jats:sc>TracerETL<\/jats:sc>\n                    , a progressive ETL framework that enables real-time analytics in standalone DBMSs through instant tuple location discovery during transformation. At its core is\n                    <jats:sc>Tracer<\/jats:sc>\n                    , a counting-based tuple tracking mechanism that constructs a\n                    <jats:italic toggle=\"yes\">tuple trace vector<\/jats:italic>\n                    using per-partition counters. This trace vector deterministically encodes each tuple's future relocation path with arrival order across transformation levels, enabling precise data access at any stage-without auxiliary indexes. We implement\n                    <jats:sc>TracerETL<\/jats:sc>\n                    in PostgreSQL and evaluate it against OLAP- and OLTP-optimized DBMSs. Experimental results show that PostgreSQL with\n                    <jats:sc>TracerETL<\/jats:sc>\n                    accelerates real-time HTAP queries by up to 127\u00d7, while efficiently handling progressive data conversion in a standalone DBMS.\n                  <\/jats:p>","DOI":"10.1145\/3769775","type":"journal-article","created":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T04:32:13Z","timestamp":1764995533000},"page":"1-28","source":"Crossref","is-referenced-by-count":0,"title":["Counting Is All You Need for Instant Tuple Discovery: Enabling Real-Time HTAP in Standalone DBMSs"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6603-2397","authenticated-orcid":false,"given":"Kyungmin","family":"Lim","sequence":"first","affiliation":[{"name":"Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2496-1591","authenticated-orcid":false,"given":"Minseok","family":"Yoon","sequence":"additional","affiliation":[{"name":"Hanyang University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4954-1454","authenticated-orcid":false,"given":"Kihwan","family":"Kim","sequence":"additional","affiliation":[{"name":"Hanyang University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3804-5450","authenticated-orcid":false,"given":"Alan","family":"Fekete","sequence":"additional","affiliation":[{"name":"The University of Sydney, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5376-7200","authenticated-orcid":false,"given":"Hyungsoo","family":"Jung","sequence":"additional","affiliation":[{"name":"Seoul National University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2020. HammerDB Version 4.3. Available at https:\/\/github.com\/TPC-Council\/HammerDB\/releases\/tag\/v4.3."},{"key":"e_1_2_1_2_1","unstructured":"Ankur Agiwal Kevin Lai Gokul Nath Babu Manoharan Indrajit Roy Jagan Sankaranarayanan Hao Zhang Tao Zou Min Chen"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-002-0074-9"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.14778\/3583140.3583157"},{"key":"e_1_2_1_5_1","unstructured":"Amazon Web Services Inc. 2023. Amazon Aurora zero-ETL Integration with Amazon Redshift. https:\/\/aws.amazon.com\/rds\/aurora\/zero-etl\/. Accessed: 2025-04-10."},{"key":"e_1_2_1_6_1","unstructured":"Amazon Web Services Inc. 2023. AWS zero-ETL. https:\/\/aws.amazon.com\/what-is\/zero-etl\/. Accessed: 2025-04-10."},{"key":"e_1_2_1_7_1","unstructured":"Oracle Corporation and\/or its affiliates. 2023. MySQL 8.0 Reference Manual: InnoDB storage engine: InnoDB and Online DDL: Online DDL Performance and Concurrency. https:\/\/dev.mysql.com\/doc\/refman\/8.0\/en\/innodb-onlineddl-performance.html."},{"key":"e_1_2_1_8_1","volume-title":"Retrieved","author":"Parquet Apache","year":"2024","unstructured":"Apache Parquet. 2024. Apache Parquet File Format. Retrieved July 28, 2024 from https:\/\/parquet.apache.org\/docs\/fileformat\/ https:\/\/parquet.apache.org\/docs\/file-format\/."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3526045"},{"key":"e_1_2_1_10_1","volume-title":"Retrieved","author":"Axboe Jens","year":"2023","unstructured":"Jens Axboe. 2023. Efficient IO with io_uring. Retrieved October 15, 2023 from https:\/\/kernel.dk\/io_uring.pdf"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3452831"},{"key":"e_1_2_1_12_1","volume-title":"TLX: Collection of Sophisticated C Data Structures, Algorithms, and Miscellaneous Helpers.","author":"Bingmann Timo","year":"2018","unstructured":"Timo Bingmann. 2018. TLX: Collection of Sophisticated C Data Structures, Algorithms, and Miscellaneous Helpers. Available at https:\/\/panthema.net\/tlx."},{"key":"e_1_2_1_13_1","unstructured":"Citus Data. 2020. Tools for running CH-benCHmark with HammerDB. https:\/\/github.com\/citusdata\/ch-benchmark."},{"key":"e_1_2_1_14_1","volume-title":"Retrieved","author":"Data Citus","year":"2024","unstructured":"Citus Data, Inc. 2024. Citus GitHub project: Distributed PostgreSQL as an extension. Retrieved February 28, 2024 from https:\/\/github.com\/citusdata\/citus https:\/\/github.com\/citusdata\/citus."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1988842.1988850"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3588726"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457551"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3064054"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196927"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3319903"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.14778\/3551793.3551853"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2463710"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/3598581.3598598"},{"key":"e_1_2_1_24_1","unstructured":"Google Inc. 2023. Google AlloyDB for PostgreSQL. https:\/\/cloud.google.com\/products\/alloydb. Accessed: 2024-04-10."},{"key":"e_1_2_1_25_1","volume-title":"Parallel Query. Retrieved","author":"The PostgreSQL Global Development Group","year":"2023","unstructured":"The PostgreSQL Global Development Group. 2023. Documentation PostgreSQL 15: Chapter 15. Parallel Query. Retrieved February 28, 2023 from https:\/\/www.postgresql.org\/docs\/15\/parallel-query.html"},{"key":"e_1_2_1_26_1","volume-title":"Retrieved","author":"The PostgreSQL Global Development Group","year":"2023","unstructured":"The PostgreSQL Global Development Group. 2023. Documentation PostgreSQL 15: Chapter 32. Just-in-Time Compilation (JIT). Retrieved February 28, 2023 from https:\/\/www.postgresql.org\/docs\/15\/jit.html"},{"key":"e_1_2_1_27_1","volume-title":"GIN (Generalized Inverted Index) Indexes. Retrieved","author":"The PostgreSQL Global Development Group","year":"2023","unstructured":"The PostgreSQL Global Development Group. 2023. Documentation PostgreSQL 15: Chapter 70. GIN (Generalized Inverted Index) Indexes. Retrieved February 28, 2023 from https:\/\/www.postgresql.org\/docs\/15\/gin.html"},{"key":"e_1_2_1_28_1","volume-title":"Github repository for LASER (ICDE'23). Retrieved","author":"Saxena Hemant","year":"2024","unstructured":"Hemant Saxena. 2024. Github repository for LASER (ICDE'23). Retrieved December 1, 2024 from https:\/\/github.com\/hemant271990\/laser-lsm-htap https:\/\/github.com\/hemant271990\/laser-lsm-htap."},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415535"},{"key":"e_1_2_1_30_1","volume-title":"Retrieved","author":"MongoDB Inc.","year":"2023","unstructured":"MongoDB Inc. 2023. MongoDB's Issue Tracker: WiredTiger [WT-6833] - Implement asynchronous IO using io_uring API. Retrieved October 15, 2023 from https:\/\/jira.mongodb.org\/browse\/WT-6833"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389714"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3526135"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2882905"},{"key":"e_1_2_1_34_1","volume-title":"The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling","author":"Kimball Ralph","unstructured":"Ralph Kimball and Margy Ross. 2002. The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (2nd ed.). John Wiley & Sons, Inc., USA.","edition":"2"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.14778\/2367502.2367518"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824071"},{"key":"e_1_2_1_37_1","volume-title":"Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (OSDI'20)","author":"Lepers Baptiste","year":"2020","unstructured":"Baptiste Lepers, Oana Balmau, Karan Gupta, and Willy Zwaenepoel. 2020. KVell: Snapshot Isolation without Snapshots. In Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (OSDI'20). USENIX Association, USA, Article 24, 17 pages."},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2013.6544834"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.14778\/3436905.3436913"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457562"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2002.1019210"},{"key":"e_1_2_1_42_1","first-page":"339","volume-title":"Proceedings of the 26th International Conference on Very Large Data Bases (VLDB '00)","author":"Manegold Stefan","unstructured":"Stefan Manegold, Peter A. Boncz, and Martin L. Kersten. 2000. What Happens During a Join? Dissecting CPU and Memory Optimization Effects. In Proceedings of the 26th International Conference on Very Large Data Bases (VLDB '00). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 339-350."},{"key":"e_1_2_1_43_1","unstructured":"Microsoft Corporation. 2025. SQL Server Computed Columns. https:\/\/learn.microsof t.com\/en-us\/previousversions\/sql\/sql-server-2008-r2\/ms191250(v=sql.105)?redirectedfrom=MSDN. Accessed: 2025-07-26."},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3526148"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/128765.128770"},{"key":"e_1_2_1_46_1","volume-title":"or its affiliates","author":"Amazon Web Services Inc.","year":"2023","unstructured":"Amazon Web Services Inc. or its affiliates. 2023. Amazon Aurora zero-ETL integration with Amazon Redshift. https:\/\/aws.amazon.com\/about-aws\/whats-new\/2023\/06\/amazon-aurora-mysql-zero-etl-integration-redshiftpublic-preview\/."},{"key":"e_1_2_1_47_1","volume-title":"Retrieved","year":"2023","unstructured":"Oracle. 2023. MySQL 8.0 Reference Manual: 15.8.6 Using Asynchronous I\/O on Linux. Retrieved October 15, 2023 from https:\/\/dev.mysql.com\/doc\/refman\/8.0\/en\/innodb-linux-native-aio.html"},{"key":"e_1_2_1_48_1","unstructured":"Oracle Corporation. 2009. Oracle Database 11g Release 2: Reference Partitioning. https:\/\/docs.oracle.com\/cd\/E11882_01\/server.112\/e25523\/part_admin001.htm. Accessed: 2024-04-10."},{"key":"e_1_2_1_49_1","unstructured":"Oracle Corporation. 2025. Oracle Virtual Columns. https:\/\/www.oracletutorial.com\/oracle-basics\/oracle-virtualcolumn. Accessed: 2025-07-26."},{"key":"e_1_2_1_50_1","unstructured":"Oracle Corporation and\/or its affiliates. 2022. Heatwave User Guide. Available at https:\/\/downloads.mysql.com\/docs\/heatwave-en.pdf."},{"key":"e_1_2_1_51_1","unstructured":"Oracle Corporation and\/or its affiliates. 2022. MySQL HeatWave: One MySQL Database for OLTP OLAP and Machine Learning. Available at https:\/\/www.oracle.com\/a\/ocom\/docs\/mysql-database-service-with-heatwave.pdf."},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1007\/s002360050048"},{"key":"e_1_2_1_53_1","volume-title":"PostgreSQL extension implements a Foreign DataWrapper (FDW) for RocksDB. Retrieved","author":"Professional Postgres","year":"2024","unstructured":"Postgres Professional. 2024. PostgreSQL extension implements a Foreign DataWrapper (FDW) for RocksDB. Retrieved December 1, 2024 from https:\/\/github.com\/postgrespro\/lsm https:\/\/github.com\/postgrespro\/lsm."},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3320212"},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132765"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3588699"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.14778\/3151106.3151108"},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536222.2536226"},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00097"},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.14778\/3685800.3685802"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196904"},{"key":"e_1_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213946"},{"key":"e_1_2_1_63_1","unstructured":"SQLite. 2025. SQLite Generated Columns. https:\/\/www.sqlite.org\/gencol.html. Accessed: 2025-07-26."},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.14778\/3598581.3598601"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.14778\/3611540.3611541"},{"key":"e_1_2_1_66_1","volume-title":"PostgreSQL: Documentation for PostgreSQL 15","author":"The PostgreSQL Global Development Group","unstructured":"The PostgreSQL Global Development Group. 2023. PostgreSQL: Documentation for PostgreSQL 15: Chapter 30.4. Asynchronous Commit. https:\/\/www.postgresql.org\/docs\/15\/wal-async-commit.html."},{"key":"e_1_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3654944"},{"key":"e_1_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3196895"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415553"},{"key":"e_1_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.14778\/3561261.3561270"}],"container-title":["Proceedings of the ACM on Management of Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3769775","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T04:55:57Z","timestamp":1781326557000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3769775"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,4]]},"references-count":70,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,12,4]]}},"alternative-id":["10.1145\/3769775"],"URL":"https:\/\/doi.org\/10.1145\/3769775","relation":{},"ISSN":["2836-6573"],"issn-type":[{"value":"2836-6573","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,4]]}}}