{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T03:43:15Z","timestamp":1752982995949,"version":"3.32.0"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:p>Microsoft Orleans is a popular open source distributed programming framework and platform which invented the virtual actor model, and has since evolved into an actor-oriented database system with the addition of database abstractions such as ACID transactions. Properties of Orleans' virtual actor model imply that any ACID transaction mechanism for operations spanning multiple actors must support distributed transactions on top of pluggable cloud storage drivers. Unfortunately, distributed transactions usually perform poorly in this environment, partly because of the high performance and contention overhead of performing two-phase commit (2PC) on slow cloud storage systems.<\/jats:p>\n          <jats:p>\n            In this paper we describe the design and implementation of ACID transactions in Orleans. The system uses two primary techniques to mask the high latency of cloud storage and enable high transaction throughput. First, Orleans pioneered the use of a distributed form of\n            <jats:italic>early lock release<\/jats:italic>\n            by releasing all of a transaction's locks during phase one of 2PC, and by tracking commit dependencies to implement cascading abort. This avoids blocking transactions while running 2PC and enables a distributed form of\n            <jats:italic>group commit.<\/jats:italic>\n            Second, Orleans leverages\n            <jats:italic>reconnaissance queries<\/jats:italic>\n            to prefetch the state of all actors involved in a transaction from cloud storage prior to running the transaction and acquiring any locks, thus ensuring no locks are held while blocking on high latency cloud storage in most cases.\n          <\/jats:p>","DOI":"10.14778\/3685800.3685801","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"3720-3730","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Cloud Actor-Oriented Database Transactions in Orleans"],"prefix":"10.14778","volume":"17","author":[{"given":"Tamer","family":"Eldeeb","sequence":"first","affiliation":[{"name":"Columbia University"}]},{"given":"Sebastian","family":"Burckhardt","sequence":"additional","affiliation":[{"name":"Microsoft Research"}]},{"given":"Reuben","family":"Bond","sequence":"additional","affiliation":[{"name":"Microsoft"}]},{"given":"Asaf","family":"Cidon","sequence":"additional","affiliation":[{"name":"Columbia University"}]},{"given":"Junfeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Columbia University"}]},{"given":"Philip A.","family":"Bernstein","sequence":"additional","affiliation":[{"name":"Microsoft Research"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2023. Akka documentation. http:\/\/akka.io\/docs."},{"key":"e_1_2_1_2_1","unstructured":"2023. Amazon DynamoDB. https:\/\/aws.amazon.com\/dynamodb\/."},{"key":"e_1_2_1_3_1","unstructured":"2023. Azure CosmosDB. https:\/\/azure.microsoft.com\/en-us\/products\/cosmos-db."},{"key":"e_1_2_1_4_1","unstructured":"2023. Google Cloud BigTable. https:\/\/cloud.google.com\/bigtable."},{"key":"e_1_2_1_5_1","unstructured":"2023. Microsoft Orleans. docs.microsoft.com\/dotnet\/orleans."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/1086.001.0001"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497466"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1810891.1810910"},{"volume-title":"14th Workshop on Hot Topics in Operating Systems (HotOS XIV)","author":"Bailis Peter","key":"e_1_2_1_9_1","unstructured":"Peter Bailis, Alan Fekete, Ali Ghodsi, Joseph M. Hellerstein, and Ion Stoica. 2013. HAT, Not CAP: Towards Highly Available Transactions. In 14th Workshop on Hot Topics in Operating Systems (HotOS XIV). USENIX Association, Santa Ana Pueblo, NM. https:\/\/www.usenix.org\/conference\/hotos13\/session\/bailis"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517349.2522732"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00010"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133931"},{"key":"e_1_2_1_13_1","unstructured":"Philip A. Bernstein Sergey Bykov Alan Geller Gabriel Kliot and Jorgen Thelin. 2014. Orleans: Distributed Virtual Actors for Programmability and Scalability. Technical Report MSR-TR-2014-41. https:\/\/www.microsoft.com\/en-us\/research\/publication\/orleans-distributed-virtual-actors-for-programmability-and-scalability\/"},{"key":"e_1_2_1_14_1","unstructured":"Philip A. Bernstein Mohammad Dashti Tim Kiefer and David Maier. 2017. Indexing in an Actor-Oriented Database. 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