{"id":15013,"date":"2024-01-18T09:33:45","date_gmt":"2024-01-18T08:33:45","guid":{"rendered":"https:\/\/sano.science\/?post_type=research&#038;p=15013"},"modified":"2024-01-18T09:33:45","modified_gmt":"2024-01-18T08:33:45","slug":"the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores","status":"publish","type":"research","link":"https:\/\/sano.science\/research\/the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores\/","title":{"rendered":"The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores"},"content":{"rendered":"\n<h2 class=\"wp-block-heading eplus-wrapper\">Maciej Besta, Robert Gerstenberger, Marc Fischer, Micha\u0142 Podstawski,\u00a0J\u00fcrgen M\u00fcller, Nils Blach, Berke Egeli, George Mitenkov,\u00a0Wojciech Chlapek, Marek Michalewicz, Torsten Hoefler<\/h2>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<p class=\"eplus-wrapper wp-block-paragraph\">Graph databases (GDBs) are crucial in academic and industry ap- plications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To tackle these challenges, we harness established practices from the HPC landscape to build a system that outperforms all past GDBs presented in the literature by orders of magnitude, for both OLTP and OLAP workloads. For this, we first identify and crystallize performance-critical building blocks in the GDB design, and ab- stract them into a portable and programmable API specification, called the Graph Database Interface (GDI), inspired by the best practices of MPI. We then use GDI to design a GDB for distributed- memory RDMA architectures. Our implementation harnesses one- sided RDMA communication and collective operations, and it offers architecture-independent theoretical performance guarantees. The resulting design achieves extreme scales of more than a hundred thousand cores. Our work will facilitate the development of next- generation extreme-scale graph databases.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n\t\n    \n        \n\t\t\t<a href=\"https:\/\/arxiv.org\/pdf\/2305.11162.pdf\" target=\"_blank\" rel= \"noopener noreferrer nofollow\" class=\"button primary \">\n\n\t\t\t\t<span>\n\t\t\t\t\tREAD HERE\n\t\t\t\t<\/span>\n\n\t\t\t<\/a>\n\n        \n    \n","protected":false},"excerpt":{"rendered":"<p>In:  International Conference for High Performance Computing, Networking, Storage and Analysis, 2023.<\/p>\n","protected":false},"featured_media":0,"template":"","research_type":[8],"research_team":[],"class_list":["post-15013","research","type-research","status-publish","hentry","research_type-publications"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.8 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores - Centre for Computational Personalized Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sano.science\/research\/the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores\" \/>\n<meta property=\"og:description\" content=\"In: International Conference for High Performance Computing, Networking, Storage and Analysis, 2023.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/research\/the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores\/\" \/>\n<meta property=\"og:site_name\" content=\"Centre for Computational Personalized Medicine\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/sano.science\/\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/sano.science\\\/research\\\/the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/research\\\/the-graph-database-interface-scaling-online-transactional-and-analytical-graph-workloads-to-hundreds-of-thousands-of-cores\\\/\",\"name\":\"The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores - 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The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To tackle these challenges, we harness established practices from the HPC landscape to build a system that outperforms all past GDBs presented in the literature by orders of magnitude, for both OLTP and OLAP workloads. For this, we first identify and crystallize performance-critical building blocks in the GDB design, and ab- stract them into a portable and programmable API specification, called the Graph Database Interface (GDI), inspired by the best practices of MPI. We then use GDI to design a GDB for distributed- memory RDMA architectures. Our implementation harnesses one- sided RDMA communication and collective operations, and it offers architecture-independent theoretical performance guarantees. The resulting design achieves extreme scales of more than a hundred thousand cores. 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