{"id":475590,"date":"2018-03-21T22:54:18","date_gmt":"2018-03-22T05:54:18","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=475590"},"modified":"2018-10-16T22:34:44","modified_gmt":"2018-10-17T05:34:44","slug":"eris-coordination-free-consistent-transactions-using-network-multi-sequencing-extended-version","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/eris-coordination-free-consistent-transactions-using-network-multi-sequencing-extended-version\/","title":{"rendered":"Eris: Coordination-Free Consistent Transactions using Network Multi-Sequencing (Extended Version)"},"content":{"rendered":"<div id=\"Eris: Coordination-Free Consistent Transactions using Network Multi-Sequencing (Extended Version)\" class=\"abstract\">Distributed storage systems aim to provide strong consistency and isolation guarantees on an architecture that is partitioned across multiple shards for scalability and replicated for fault-tolerance. Traditionally, achieving all of these goals has required an expensive combination of atomic commitment and replication protocols &#8212; introducing extensive coordination overhead. Our system, Eris, takes a very different approach. It moves a core piece of concurrency control functionality, which we term <em>multi-sequencing<\/em>, into the datacenter network itself. This network primitive takes on the responsibility for consistently ordering transactions, and a new lightweight transaction protocol ensures atomicity.<\/div>\n<div><\/div>\n<div class=\"abstract\">The end result is that Eris avoids both replication and transaction coordination overhead: we show that it can process a large class of distributed transactions <em>in a single round-trip<\/em> from the client to the storage system <em>without any explicit coordination<\/em> between shards or replicas. It provides atomicity, consistency, and fault-tolerance with less than 10% overhead &#8212; achieving throughput 4.5&#8211;35x higher and latency 72&#8211;80% lower than a conventional design on standard benchmarks.<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Distributed storage systems aim to provide strong consistency and isolation guarantees on an architecture that is partitioned across multiple shards for scalability and replicated for fault-tolerance. Traditionally, achieving all of these goals has required an expensive combination of atomic commitment and replication protocols &#8212; introducing extensive coordination overhead. Our system, Eris, takes a very different [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193718],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-475590","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"University of Washington","msr_edition":"Technical Report UW-CSE-TR-17-10-01","msr_affiliation":"","msr_published_date":"2017-10-27","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"UW-CSE-TR-17-10-01","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"XMLSEC '02 Proceedings of the 2002 ACM workshop on XML security","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"475593","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"eris-tr17","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2018\/03\/eris-tr17.pdf","id":475593,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Jialin Li","user_id":0,"rest_url":false},{"type":"text","value":"Ellis Michael","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Dan R. K. Ports","user_id":37404,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Dan R. K. Ports"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144927],"msr_project":[617940],"publication":[],"video":[],"download":[],"msr_publication_type":"techreport","related_content":{"projects":[{"ID":617940,"post_title":"Prometheus","post_name":"prometheus-microsoft-research","post_type":"msr-project","post_date":"2019-10-28 12:28:14","post_modified":"2022-04-21 15:55:10","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/prometheus-microsoft-research\/","post_excerpt":"Project Prometheus is building faster, more efficient datacenter systems by co-designing distributed systems with new network primitives. 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