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<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
<channel>
<title>Linked Data Benchmark Council</title>
<link>https://ldbcouncil.org/</link>
<description>Recent content on Linked Data Benchmark Council</description>
<generator>Hugo -- gohugo.io</generator>
<language>en-us</language>
<lastBuildDate>Fri, 13 Dec 2024 13:00:00 +0000</lastBuildDate><atom:link href="https://ldbcouncil.org/index.xml" rel="self" type="application/rss+xml" />
<item>
<title>Nineteenth TUC Meeting</title>
<link>https://ldbcouncil.org/event/nineteenth-tuc-meeting/</link>
<pubDate>Fri, 13 Dec 2024 13:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/event/nineteenth-tuc-meeting/</guid>
<description><p><strong>Organizers:</strong> Alastair Green, Gábor Szárnyas, Benjamin Steer</p>
<p>LDBC is hosting half-day hybrid TUC meeting co-located in <strong>London</strong> on <strong>December 13 (Friday)</strong>.</p>
<p>The program consists of 15-minute talks followed by a short Q&amp;A session.
If you would like to participate (in person or remote), consider registering using <a href="https://forms.gle/1qYBiiFxrv2qRbpL7">our form</a> – but walk-ins are also welcome!</p>
<h3 id="program">Program</h3>
<p><strong>Location:</strong> <a href="https://maps.app.goo.gl/Mr6TJsD4zZvhbrqy9">Andaz London Liverpool Street</a>, Fenchurch room (first floor)</p>
<table>
<thead>
<tr>
<th>Start (GMT)</th>
<th>Finish (GMT)</th>
<th>Speaker(s)</th>
<th>Title</th>
</tr>
</thead>
<tbody>
<tr>
<td>13:00</td>
<td>13:15</td>
<td>Alastair Green (LDBC)</td>
<td>Introducing a showcase of the work of LDBC</td>
</tr>
<tr>
<td>13:15</td>
<td>13:35</td>
<td>Florian Fan (Ant Group)</td>
<td><a href="https://youtu.be/HSOrIlR4WSA">AntGroup GraphRAG: The graph+AI technology advancement on TuGraph</a></td>
</tr>
<tr>
<td>13:35</td>
<td>13:55</td>
<td>Yun Zhu (Zhejiang University and Ant Group)</td>
<td><a href="https://youtu.be/Hgm5D-AoRW8">Graph retrieval-augmented generation: A survey</a></td>
</tr>
<tr>
<td>13:55</td>
<td>14:15</td>
<td>Henry Gabb and Gabor Szarnyas (LDBC)</td>
<td>LDBC benchmarks, auditing and fair use: Process and prospects</td>
</tr>
<tr>
<td>14:15</td>
<td>14:35</td>
<td>Shipeng Qi (Ant Group)</td>
<td><a href="https://youtu.be/Blx0XNdBeaY">LDBC Financial Benchmark</a></td>
</tr>
<tr>
<td>14:35</td>
<td>14:55</td>
<td><em>(Break)</em></td>
<td></td>
</tr>
<tr>
<td>14:55</td>
<td>15:20</td>
<td>Ora Lassila (AWS)</td>
<td>RDF and Property Graphs, the ontology/schema landscape</td>
</tr>
<tr>
<td>15:20</td>
<td>15:40</td>
<td>Charlie Ivie (AWS + Graph.Build)</td>
<td><a href="https://youtu.be/idQKCjLHLpk">Graph.Build</a></td>
</tr>
<tr>
<td>15:40</td>
<td>16:05</td>
<td>Alastair Green (LDBC) and Dušan Živković (Bloomberg)</td>
<td><a href="https://youtu.be/xTtSKsTCwvI">The future of property graph schema + JSON schema demo</a></td>
</tr>
<tr>
<td>16:05</td>
<td>16:25</td>
<td>Oskar van Rest (Oracle)</td>
<td><a href="https://youtu.be/q0Zte_FMQI0">The SQL/PGQ Standard and its support in Oracle Database 23ai</a></td>
</tr>
<tr>
<td>16:25</td>
<td>16:40</td>
<td><em>(Break)</em></td>
<td></td>
</tr>
<tr>
<td>16:40</td>
<td>17:00</td>
<td>Malcolm Crowe</td>
<td><a href="https://youtu.be/F7lZlK5qFFE">PyrrhoDBMS: Implementing GQL</a></td>
</tr>
<tr>
<td>17:00</td>
<td>17:20</td>
<td>Keith Hare (JCC)</td>
<td><a href="https://youtu.be/TbLpXCy-BX8">What&rsquo;s next for the GQL standard?</a></td>
</tr>
<tr>
<td>17:20</td>
<td>17:40</td>
<td>Michael Burbidge</td>
<td><a href="https://youtu.be/s7ua8qtEZj0">openGQL tooling and collaboration with Strumenta</a></td>
</tr>
<tr>
<td>17:40</td>
<td>18:00</td>
<td>Daniel ten Wolde (CWI)</td>
<td><a href="https://youtu.be/Fzci3Ic0RBQ">DuckPGQ: SQL/PGQ in DuckDB</a></td>
</tr>
</tbody>
</table>
<h4 id="tuc-event-locations">TUC event locations</h4>
<p>We maintain a <a href="https://www.google.com/maps/d/u/0/edit?mid=19_fi4fV-3-PZkNWCCcmhU86ct2EZXbgo">map of the LDBC TUC events</a> we hosted so far.</p>
</description>
</item>
<item>
<title>Eighteenth TUC Meeting</title>
<link>https://ldbcouncil.org/event/eighteenth-tuc-meeting/</link>
<pubDate>Fri, 30 Aug 2024 09:00:00 -0800</pubDate>
<guid>https://ldbcouncil.org/event/eighteenth-tuc-meeting/</guid>
<description><p><strong>Organizers:</strong> Shipeng Qi, Wenyuan Yu (Alibaba Damo), Yan Zhou (CreateLink)</p>
<p>LDBC is hosting a <strong>two-day</strong> hybrid workshop, co-located in <strong>Guangzhou</strong> with <a href="https://vldb.org/2024/">VLDB 2024</a> on <strong>August 30-31 (Friday-Saturday)</strong>.</p>
<p>The program consists of 10- and 15-minute talks followed by a Q&amp;A session. The talks will be recorded and made available
online. <strong>If you would like to participate please register using <a href="https://forms.gle/aVPrrcxXpSwrWPnh6">our form</a>.</strong></p>
<p>LDBC will host a <strong>social event</strong> on Friday at the <a href="https://www.marriott.com/en-us/hotels/canwi-the-westin-pazhou/overview/">3F Xingang Room, the Westin Pazhou,
Guangzhou</a>. The address is <a href="https://www.google.com/maps/search/?api=1&amp;query=23.09611%2C113.363612&amp;hl=en-US">Area C, Canton Fair Complex, 681 Fengpu Zhong Rd., Haizhu District, Guangzhou, Guangdong</a></p>
<p>In addition, Ant Group, Alibaba Damo, and CreateLink will host a <strong>Happy Hour</strong> on Saturday. Join us by the Pearl River at the Vino Restaurant, located on the <a href="https://www.google.com/maps/place/Pati+Beer+Cultural+Art+Area/@23.10676,113.3395851,17z/data=!3m1!4b1!4m6!3m5!1s0x3402ff9921d813ff:0x47f2671cfc7a6eec!8m2!3d23.10676!4d113.34216!16s%2Fg%2F11rcyt04t8?hl=en&amp;entry=ttu">8th Floor, No. 118 Modiesha Street, Area B, Beer Culture Creative Art District, Guangzhou</a>.</p>
<h3 id="program-and-slides">Program and Slides</h3>
<p>This event is hosted in Guangzhou. Local time is <strong>CST (China Standard time) on the first column</strong>. <strong>CEST (Central European Standard time) on the third column</strong> and <strong>PDT (Pacific Daylight time) on the forth column</strong> are listed in addition for the participants in European and Pacific timezone.</p>
<h4 id="august-30-friday">August 30, Friday</h4>
<p><strong>Location:</strong> <a href="https://www.langhamhotels.com/en/the-langham/guangzhou/">Langham Place</a>, Guangzhou, <strong>room 1</strong>,
co-located with VLDB (N0.630-638 Xingang Dong Road, Haizhu District, Guangzhou, China). See the map <a href="https://maps.app.goo.gl/86jD3Dy9Aa7bwLs36">here</a>.</p>
<table>
<thead>
<tr>
<th>CST Start</th>
<th>CST End</th>
<th>CEST Start</th>
<th>PDT Start</th>
<th>Speaker</th>
<th>Topic</th>
</tr>
</thead>
<tbody>
<tr>
<td>09:00</td>
<td>09:20</td>
<td>03:00</td>
<td>18:00</td>
<td>Alastair Green (LDBC)</td>
<td>State of the Union - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/1.%20LDBC%20_State%20of%20the%20Union_%20--%2018th%20TUC,%20Guangzhou,%202024-08-30%20Alastair%20Green.pdf">slides</a> - <a href="https://youtu.be/I0R72mAKQMQ">video</a></td>
</tr>
<tr>
<td>09:20</td>
<td>09:40</td>
<td>03:20</td>
<td>18:20</td>
<td>Lei Zou (Peking University)</td>
<td>Unified Graph Query Plan Representation and Optimization - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/2.%20Unified%20Graph%20Query%20Plan%20Representation%20and%20Optimization.pdf">slides</a> - <a href="https://youtu.be/fzsQ--DW49k">video</a></td>
</tr>
<tr>
<td>09:40</td>
<td>10:00</td>
<td>03:40</td>
<td>18:40</td>
<td>Wei Wang (East China Normal University)</td>
<td>From OpenRank to OpenPerf: Enhancing Open-Source Ecosystem Insights with Graph-Based Approaches - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/3.%20From%20OpenRank%20to%20OpenPerf.pdf">slides</a> - <a href="https://youtu.be/XKGJ0VPtadg">video</a></td>
</tr>
<tr>
<td>10:00</td>
<td>10:20</td>
<td>04:00</td>
<td>19:00</td>
<td>coffee break</td>
<td></td>
</tr>
<tr>
<td>10:20</td>
<td>10:40</td>
<td>04:20</td>
<td>19:20</td>
<td>Keith W. Hare (JCC / WG3)</td>
<td>The GQL Standard is Published! Now what? - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/4.%20GQL%20standard%20is%20published%202024-08-30.pdf">slides</a> - <a href="https://youtu.be/RoebDzkbn9c">video</a></td>
</tr>
<tr>
<td>10:40</td>
<td>11:10</td>
<td>04:40</td>
<td>19:40</td>
<td>Michael Burbidge (LDBC), co-present with <br>Alessio Stalla, Federico Tomassetti, Tracey Walsh</td>
<td>The LDBC GQL Implementation Working Group mission and progress - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/5.%20GQL%20Implementation%20WG.pdf">slides</a> - <a href="https://youtu.be/WTT6X7zQisg">video</a></td>
</tr>
<tr>
<td>11:10</td>
<td>11:30</td>
<td>05:10</td>
<td>20:10</td>
<td>Oskar Van Rest (Oracle)</td>
<td>The SQL/PGQ Standard: SQL support for property graphs - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/6.%20PGQ%20Standard%20final.pdf">slides</a> - <a href="https://youtu.be/wvXm0wgkrF8">video</a></td>
</tr>
<tr>
<td>11:30</td>
<td>12:00</td>
<td>05:30</td>
<td>20:30</td>
<td>Peter Boncz (CWI / LDBC)</td>
<td>The state of DuckPGQ - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/7.%20The%20State%20of%20DuckPGQ.pdf">slides</a> - <a href="https://youtu.be/ZlXu0UM2LUw">video</a></td>
</tr>
<tr>
<td>12:00</td>
<td>13:00</td>
<td>06:00</td>
<td>21:00</td>
<td>lunch at Langham hotel</td>
<td></td>
</tr>
<tr>
<td>13:00</td>
<td>13:20</td>
<td>07:00</td>
<td>22:00</td>
<td>Xuntao Cheng (vesoft)</td>
<td>GQL and its implementation - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/8.%20GQL_talk_Xuntao_Cheng.pdf">slides</a> - <a href="https://youtu.be/XsRxw06B-jY">video</a></td>
</tr>
<tr>
<td>13:20</td>
<td>13:40</td>
<td>07:20</td>
<td>22:20</td>
<td>Alastair Green (JCC / LDBC)</td>
<td>LEX: The future of Graph Schema - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/9.%20LEX-074%20LEX%20LDBC%2018th%20LDBC%20TUC%20%20%2030%20August%202024.pdf">slides</a> - <a href="https://youtu.be/txskwX2DwxA">video</a></td>
</tr>
<tr>
<td>13:40</td>
<td>14:00</td>
<td>07:40</td>
<td>22:40</td>
<td>Valerio Malenchino (Neo4j)</td>
<td>OpenCypher, a path to GQL. – <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/10.%20openCypher,%20a%20path%20to%20GQL.pdf">slides</a> - <a href="https://youtu.be/qm7ViOYfwgY">video</a></td>
</tr>
<tr>
<td>14:00</td>
<td>14:55</td>
<td>08:00</td>
<td>23:00</td>
<td>Host: Alastair Green (JCC / LDBC), panelists: Peter Boncz (CWI / LDBC), Chuntao Hong (AntGroup), Mingxi Wu (TigerGraph), Xuntao Cheng(vesoft)</td>
<td>ISO GQL Panel - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/11.%20Panel%20questions.pdf">slides</a> - <a href="https://youtu.be/qVcQYYbx71g">video</a></td>
</tr>
<tr>
<td>14:55</td>
<td>15:15</td>
<td>08:55</td>
<td>23:55</td>
<td>coffee break</td>
<td></td>
</tr>
<tr>
<td>15:15</td>
<td>15:35</td>
<td>09:15</td>
<td>00:15</td>
<td>Shixuan Sun (Shanghai Jiao Tong University)</td>
<td>FaaSGraph: Enabling Scalable, Efficient, and Cost-Effective Graph Processing with Serverless Computing - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/12.%20FaaSGraph-ShixuanSun-LDBC.pdf">slides</a> - <a href="https://youtu.be/c-KxJLcyzto">video</a></td>
</tr>
<tr>
<td>15:35</td>
<td>15:55</td>
<td>09:35</td>
<td>00:35</td>
<td>Cheng Chen (ByteDance)</td>
<td>BG3: A Cost Effective and I/O Efficient Graph Database in ByteDance - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/13.%20bg3-ldbc24.pdf">slides</a> - <a href="https://youtu.be/pFUbg34lvPo">video</a></td>
</tr>
<tr>
<td>15:55</td>
<td>16:15</td>
<td>09:55</td>
<td>00:55</td>
<td>Mingxi Wu (TigerGraph)</td>
<td>TigerGraph: Key Lessons from Running SNB BI Workload on Large-Scale Data Set - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/14.%20LDBC-SNB-108T-2024-Aug.pdf">slides</a> - <a href="https://youtu.be/9XiOL7fjz0k">video</a></td>
</tr>
<tr>
<td>16:15</td>
<td>16:35</td>
<td>10:15</td>
<td>01:15</td>
<td>Gabor Szarnyas (DuckDB / LDBC)</td>
<td>The LDBC benchmark suite - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/15.%20gabor-szarnyas-the-ldbc-benchmark-suite.pdf">slides</a> - <a href="https://youtu.be/j6C4G0O-bQM">video</a></td>
</tr>
<tr>
<td>16:35</td>
<td>16:55</td>
<td>10:35</td>
<td>01:35</td>
<td>Shipeng Qi (AntGroup / LDBC)</td>
<td>The LDBC Financial Benchmark - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day1/16.%20The%20LDBC%20FinBench%20v0.2.0.pdf">slides</a> - <a href="https://youtu.be/hTfK-9Toor4">video</a></td>
</tr>
<tr>
<td>16:55</td>
<td>17:40</td>
<td>10:55</td>
<td>01:55</td>
<td>In-person participants</td>
<td>LDBC Voting Members Meeting</td>
</tr>
<tr>
<td>18:00</td>
<td>22:00</td>
<td>12:00</td>
<td>03:00</td>
<td>Dinner at 3/F Xingang Room, the Westin Pazhou, Guangzhou</td>
<td></td>
</tr>
</tbody>
</table>
<h4 id="august-31-saturday">August 31, Saturday</h4>
<p><strong>Location:</strong> Alibaba Center, Guangzhou (N0.88 Dingxin Road, Haizhu District, Guangzhou, China), near to VLDB Langham Place. See the map <a href="https://maps.app.goo.gl/HgEVafZMRmrzUsgW8">here</a>.</p>
<table>
<thead>
<tr>
<th>CST Start</th>
<th>CST End</th>
<th>CEST Start</th>
<th>PDT Start</th>
<th>Speaker</th>
<th>Topic</th>
</tr>
</thead>
<tbody>
<tr>
<td>09:00</td>
<td>09:20</td>
<td>03:00</td>
<td>18:00</td>
<td>Ora Lassila (AWS Neptune)</td>
<td>Aligning RDF and LPGs: A Status Report of the OneGraph Initiative - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/1.%20onegraph-ldbc-tuc18-202408-final.pdf">slides</a> - <a href="https://youtu.be/to_dWaaX498">video</a></td>
</tr>
<tr>
<td>09:20</td>
<td>09:40</td>
<td>03:20</td>
<td>18:20</td>
<td>Xiangyu Ke (Zhejiang University)</td>
<td>View-based explanation for graph neural networks - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/2.%20GVEX-XiangyuKE.pdf">slides</a> - <a href="https://youtu.be/EgojnYfRuuw">video</a></td>
</tr>
<tr>
<td>09:40</td>
<td>10:00</td>
<td>03:40</td>
<td>18:40</td>
<td>Chengying Huan (Insitute of software, CAS)</td>
<td>Hybrid Sampling Algorithm for Dynamic Graph Sampling - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/3.%20Dynamic_sampling.pdf">slides</a> - <a href="https://youtu.be/sOuz2MYZYoI">video</a></td>
</tr>
<tr>
<td>10:00</td>
<td>10:20</td>
<td>04:00</td>
<td>19:00</td>
<td>Chen Zhang (CreateLink)</td>
<td>Parameterized Algorithm Routine: The Perfect Balance between Performance and Usability - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/4.%20TUC_Galaxybase.pdf">slides</a> - <a href="https://youtu.be/d4wPsf4pyCE">video</a></td>
</tr>
<tr>
<td>10:20</td>
<td>10:50</td>
<td>04:20</td>
<td>19:20</td>
<td>coffee break</td>
<td></td>
</tr>
<tr>
<td>10:50</td>
<td>11:10</td>
<td>04:50</td>
<td>19:50</td>
<td>Long Yuan (Nanjing University of Science and Technology)</td>
<td>Revisit benchmarking graph analytics - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/5.%20Revisiting%20Graph%20Analytics%20Benchmarks.pdf">slides</a> - <a href="https://youtu.be/9VOX3th7fV4">video</a></td>
</tr>
<tr>
<td>11:10</td>
<td>11:30</td>
<td>05:10</td>
<td>20:10</td>
<td>Longbin Lai (Alibaba Group)</td>
<td>A Graph-Native Query Optimization Framework - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/6.%20GOPT-TUC-v0.2.pdf">slides</a> - <a href="https://youtu.be/De39jeVmif8">video</a></td>
</tr>
<tr>
<td>11:30</td>
<td>11:50</td>
<td>05:30</td>
<td>20:30</td>
<td>Jingbo Xu (Alibaba Group)</td>
<td>Apache GraphAr: An Open-Source Standard File Format for Graph Data Storage and Retrieval - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/7.%20GraphAr-TUCv1.pdf">slides</a> - <a href="https://youtu.be/tGx5MUghofc">video</a></td>
</tr>
<tr>
<td>11:50</td>
<td>12:10</td>
<td>05:50</td>
<td>20:50</td>
<td>Sijie Shen (Alibaba Group)</td>
<td>Introducing GART: Real-Time Online Graph Data Analysis for SQL - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/8.%20GART.pdf">slides</a> - <a href="https://youtu.be/pMVUc72BdpQ">video</a></td>
</tr>
<tr>
<td>12:10</td>
<td>13:30</td>
<td>06:10</td>
<td>21:10</td>
<td>lunch at Alibaba Center</td>
<td></td>
</tr>
<tr>
<td>13:30</td>
<td>13:50</td>
<td>07:30</td>
<td>22:30</td>
<td>Atanas Kiryakov (OntoText)</td>
<td>Graph RAG Varieties - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/9.%20Graph%20RAG%20Varieties%20-%20LDBC.pdf">slides</a> - <a href="https://youtu.be/dFyPlllOm1s">video</a></td>
</tr>
<tr>
<td>14:10</td>
<td>14:30</td>
<td>08:10</td>
<td>23:10</td>
<td>Boci Peng (AntGroup)</td>
<td>Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/11.%20SEPTA_tuc_pbc.pdf">slides</a> - <a href="https://youtu.be/hZwkbLoOcUA">video</a></td>
</tr>
<tr>
<td>14:30</td>
<td>14:50</td>
<td>08:30</td>
<td>23:30</td>
<td>Damien Hilloulin (Oracle Labs)</td>
<td>Graphs, Graph-RAG, and LLMs: An Introduction - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/12.%202024-08-31-GraphsGraph-RAGsandLLMsAnIntroduction-tuc.pdf">slides</a> - <a href="https://youtu.be/ENCso_xlNgQ">video</a></td>
</tr>
<tr>
<td>14:50</td>
<td>15:20</td>
<td>08:50</td>
<td>23:50</td>
<td>coffee break</td>
<td></td>
</tr>
<tr>
<td>15:20</td>
<td>15:50</td>
<td>09:20</td>
<td>00:20</td>
<td>Xiyang (Kuzu Inc.)</td>
<td>Progress and Roadmap of the Kuzu Graph DBMS - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/13.%20Kuzu%20TUC%20Meeting%20Aug%202024.pdf">slides</a> - <a href="https://youtu.be/m7cSJRa__t4">video</a></td>
</tr>
<tr>
<td>15:50</td>
<td>16:10</td>
<td>09:50</td>
<td>00:50</td>
<td>Ricky Sun (Ultipa)</td>
<td>A Graph Analytics Supercharge Case Study of GPU vs. CPU on Performance, Greenness and Cost - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/14.%20A%20Graph%20Analytics%20Supercharge%20Case%20Study%20of%20CPU%20vs.%20GPU%20on%20Performance,%20Cost%20and%20ESG%20v2.pdf">slides</a> - <a href="https://youtu.be/ay_4SAY_PPo">video</a></td>
</tr>
<tr>
<td>16:10</td>
<td>16:30</td>
<td>10:10</td>
<td>01:10</td>
<td>Min Wu (Fabarta)</td>
<td>ArcNeural: A Multi-Modal Database for the Gen-AI Era - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/15.%20Fabarta.pdf">slides</a> - <a href="https://youtu.be/opmyhgkIYok">video</a></td>
</tr>
<tr>
<td>16:30</td>
<td>16:50</td>
<td>10:30</td>
<td>01:30</td>
<td>Juan Yang (StarGraph)</td>
<td>AtlasGraph: A High-Performance Graph Database Solution for Complex Data Challenges - <a href="https://datasets.ldbcouncil.org/event/eighteenth-tuc-meeting/day2/16.%20StarGraph%202024%20VLDB%202024-08-31.pdf">slides</a> - <a href="https://youtu.be/iF7KFref9Rs">video</a></td>
</tr>
<tr>
<td>18:00</td>
<td>22:00</td>
<td>12:00</td>
<td>03:00</td>
<td>Happy Hour sponsored by AntGroup, Alibaba Damo, CreateLink</td>
<td></td>
</tr>
</tbody>
</table>
<h4 id="tuc-event-locations">TUC event locations</h4>
<p>A <a href="https://www.google.com/maps/d/u/0/edit?mid=19_fi4fV-3-PZkNWCCcmhU86ct2EZXbgo">map of the LDBC TUC events</a> we hosted so far.</p>
</description>
</item>
<item>
<title>Seventeenth TUC Meeting</title>
<link>https://ldbcouncil.org/event/seventeenth-tuc-meeting/</link>
<pubDate>Sun, 09 Jun 2024 09:00:00 -0400</pubDate>
<guid>https://ldbcouncil.org/event/seventeenth-tuc-meeting/</guid>
<description><p><strong>Organizers:</strong> Renzo Angles, Sebastián Ferrada</p>
<p>LDBC is hosting a one-day in-person workshop, co-located in <strong>Santiago de Chile</strong> with <a href="https://2024.sigmod.org/venue.shtml">SIGMOD 2024</a> on <strong>June 9 (Sunday)</strong>.</p>
<p>The workshop will be held in the <strong>Hotel Plaza El Bosque Ebro</strong> (<a href="https://www.plazaelbosque.cl">https://www.plazaelbosque.cl</a>), which is two blocks away from SIGMOD&rsquo;s venue. See the map <a href="https://maps.app.goo.gl/78oiw3zo2pH3gy5R6">here</a>.</p>
<h3 id="program">Program</h3>
<p><strong>All times are in Chile time (GMT-4).</strong></p>
<p><strong>Each speaker will have 20 minutes for exposition plus 5 minutes for questions.</strong></p>
<table>
<thead>
<tr>
<th>Time</th>
<th>Speaker</th>
<th>Title</th>
</tr>
</thead>
<tbody>
<tr>
<td>09:00</td>
<td>Renzo Angles (U. Talca)</td>
<td>Welcome</td>
</tr>
<tr>
<td>09:30</td>
<td>Alastair Green (LDBC Vice-chair)</td>
<td>Status of the LDBC Extended GQL Schema Working Group</td>
</tr>
<tr>
<td>10:00</td>
<td>Hannes Voigt (Neo4j)</td>
<td>Inside the Standardization Machine Room: How ISO/IEC 39075:2024 GQL was produced - <a href="https://ldbcouncil.org/docs/tuc17th/inside.pdf">slides</a> - <a href="https://youtu.be/EpwHzPSOF3o">video</a></td>
</tr>
<tr>
<td>10:30</td>
<td>Calin Iorgulescu (Oracle)</td>
<td>PGX.D: Distributed graph processing engine</td>
</tr>
<tr>
<td>11:00</td>
<td>Coffee break</td>
<td></td>
</tr>
<tr>
<td>11:30</td>
<td>Ricky Sun (Ultipa, Inc.)</td>
<td>A Unified Graph Framework with SCC (Storage-Compute Coupled) and HDC (High-Density Computing) Clustering</td>
</tr>
<tr>
<td>12:00</td>
<td>Daan de Graaf (TU Eindhoven)</td>
<td>Algorithm Support in a Graph Database, Done Right - <a href="https://ldbcouncil.org/docs/tuc17th/graphalg.pdf">slides</a> - <a href="https://youtu.be/eys5wJmy2PY">video</a></td>
</tr>
<tr>
<td>12:30</td>
<td>Angela Bonifati (Lyon 1 University and IUF, France)</td>
<td>Transforming Property Graphs</td>
</tr>
<tr>
<td>13:00</td>
<td>Brunch</td>
<td></td>
</tr>
<tr>
<td>14:00</td>
<td>Juan Sequeda (data.world)</td>
<td>A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model&rsquo;s Accuracy for Question Answering on Enterprise SQL Databases - <a href="https://youtu.be/P0WoWFp1fN8">video</a></td>
</tr>
<tr>
<td>14:30</td>
<td>Olaf Hartig (Linköping University)</td>
<td>FedShop: A Benchmark for Testing the Scalability of SPARQL Federation Engines - <a href="https://ldbcouncil.org/docs/tuc17th/fedshop.pdf">slides</a> - <a href="https://youtu.be/J7rAowKmAcE">video</a></td>
</tr>
<tr>
<td>15:00</td>
<td>Olaf Hartig (Amazon)</td>
<td>Datatypes for Lists and Maps in RDF Literals</td>
</tr>
<tr>
<td>15:30</td>
<td>Peter Boncz (CWI and MotherDuck)</td>
<td>The state of DuckPGQ - <a href="https://ldbcouncil.org/docs/tuc17th/duckpgq.pdf">slides</a> - <a href="https://youtu.be/VoxV0z_XQPM">video</a></td>
</tr>
<tr>
<td>16:00</td>
<td>Coffee break</td>
<td></td>
</tr>
<tr>
<td>16:30</td>
<td>Juan Reutter (IMFD and PUC Chile)</td>
<td>MillenniumDB: A Persistent, Open-Source, Graph Database</td>
</tr>
<tr>
<td>17:00</td>
<td>Carlos Rojas (IMFD)</td>
<td>WDBench: A Wikidata Graph Query Benchmark</td>
</tr>
<tr>
<td>17:30</td>
<td>Sebastián Ferrada (IMFD and Univ. de Chile)</td>
<td>An algebra for evaluating path queries</td>
</tr>
<tr>
<td>19:30</td>
<td>Dinner</td>
<td></td>
</tr>
</tbody>
</table>
</description>
</item>
<item>
<title>Record-Breaking SNB Interactive Results for GraphScope</title>
<link>https://ldbcouncil.org/post/record-breaking-snb-interactive-results-for-graphscope/</link>
<pubDate>Sun, 26 May 2024 00:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/post/record-breaking-snb-interactive-results-for-graphscope/</guid>
<description><p>We are happy to annonunce new <a href="https://ldbcouncil.org/benchmarks/snb-interactive/">audited results for the SNB Interactive workload</a>, achieved by the open-source <a href="https://github.com/alibaba/GraphScope">GraphScope Flex</a> system.</p>
<p>The current audit of the system has broken several records:</p>
<ul>
<li>It achieved 130.1k ops/s on scale factor 100, compared to the previous record of 48.8k ops/s.</li>
<li>It achieved 131.3k ops/s on scale factor 300, compared to the previous record of 48.3k ops/s.</li>
<li>It is the first system to successfully complete the benchmark on scale factor 1000. It achieved a throughput of 127.8k ops/s</li>
</ul>
<p>The audit was commissioned by the <a href="https://www.alibabacloud.com/">Alibaba Cloud</a> and was conducted by <a href="https://www.linkedin.com/in/arnau-prat-a70283bb/">Dr. Arnau Prat-Pérez</a>, one of the original authors of the SNB Interactive benchmark. The queries were implemented as C++ stored procedures and the benchmark was executed on the Alibaba Cloud&rsquo;s infrastructure. The <a href="https://ldbcouncil.org/benchmarks/snb/LDBC_SNB_I_20240514_SF100-300-1000_graphscope-executive_summary.pdf">executive summary</a>, <a href="https://ldbcouncil.org/benchmarks/snb/LDBC_SNB_I_20240514_SF100-300-1000_graphscope.pdf">full disclosure report</a>, and <a href="https://datasets.ldbcouncil.org/audits/LDBC_SNB_I_20240514_SF100-300-1000_graphscope-attachments.tar.gz">supplementary package</a> describe the benchmark&rsquo;s steps and include instructions for reproduction.</p>
<p>LDBC would like to congratulate the GraphScope Flex team on their record-breaking results.</p>
<div align="center"><img src="https://ldbcouncil.org/images/graphscope.svg" width="200"></div>
</description>
</item>
<item>
<title>Launching open-source language tools for ISO/IEC GQL</title>
<link>https://ldbcouncil.org/post/ldbc-announces-open-source-gql-tools/</link>
<pubDate>Thu, 09 May 2024 00:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/post/ldbc-announces-open-source-gql-tools/</guid>
<description><p>Following the publication of ISO/IEC GQL (graph query language) in April 2024, LDBC today launches open-source language engineering tools to help implementers, and assist in generation of code examples and tests for the GQL language. See this <a href="https://ldbcouncil.org/pages/opengql-announce">announcement from Alastair Green, Vice-chair of LDBC</a>.</p>
<p>These tools are the work of the <strong>LDBC GQL Implementation Working Group</strong>, headed up by Michael Burbidge. Damian Wileński and Dominik Tomaszuk have worked with Michael to create these artefacts based on his ANTLR grammar for GQL.</p>
</description>
</item>
<item>
<title>Announcing the Official Release of LDBC Financial Benchmark v0.1.0</title>
<link>https://ldbcouncil.org/post/announcing-the-official-release-of-ldbc-financial-benchmark/</link>
<pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/post/announcing-the-official-release-of-ldbc-financial-benchmark/</guid>
<description><p>We are delighted to announce the official release of the initial version (v0.1.0) of <a href="https://ldbcouncil.org/benchmarks/finbench/">Financial Benchmark (FinBench)</a>.</p>
<p>The Financial Benchmark (FinBench) project defines a graph database benchmark targeting financial scenarios such as anti-fraud and risk control. It is maintained by the <a href="https://ldbcouncil.org/benchmarks/finbench/ldbc-finbench-work-charter.pdf">LDBC FinBench Task Force</a>. The benchmark has one workload currently, <strong>Transaction Workload</strong>, capturing OLTP scenario with complex read queries that access the neighbourhood of a given node in the graph and write queries that continuously insert or delete data in the graph.</p>
<p>Compared to LDBC SNB, the FinBench differs in application scenarios, data patterns, and workloads, resulting in different schema characteristics, latency bounds, path filters, etc. For a brief overview, see the <a href="https://ldbcouncil.org/benchmarks/finbench/finbench-talk-16th-tuc.pdf">slides</a> in the 16th TUC. The <a href="https://arxiv.org/pdf/2306.15975.pdf">Financial Benchmark&rsquo;s specification</a> can be found on arXiv.</p>
<p>The release of FinBench initial version (v0.1.0) was approved by LDBC on June 23, 2023. It is the good beginning of FinBench. In the future, the FinBench Task Force will polish the benchmark continuously.</p>
<p>If you are interested in joining FinBench Task Force, please reach out at info at ldbcouncil.org or qishipeng.qsp at antgroup.com.</p>
</description>
</item>
<item>
<title>Sixteenth TUC Meeting</title>
<link>https://ldbcouncil.org/event/sixteenth-tuc-meeting/</link>
<pubDate>Fri, 23 Jun 2023 09:00:00 -0800</pubDate>
<guid>https://ldbcouncil.org/event/sixteenth-tuc-meeting/</guid>
<description><p><strong>Organizers:</strong> Oskar van Rest, Alastair Green, Gábor Szárnyas</p>
<p>LDBC is hosting a <strong>two-day</strong> hybrid workshop, co-located with <a href="https://2023.sigmod.org/venue.shtml">SIGMOD 2023</a> on <strong>June 23-24 (Friday-Saturday)</strong>.</p>
<p>The program consists of 10- and 15-minute talks followed by a Q&amp;A session. The talks will be recorded and made available online. <strong>If you would like to participate please register using <a href="https://forms.gle/T6bwVHzK9V5FaKyR9">our form</a>.</strong></p>
<p>LDBC will host a <strong>social event</strong> on Friday at the <a href="https://www.blackbottleseattle.com/">Black Bottle gastrotavern</a> in Belltown: <a href="https://goo.gl/maps/hQzBRR2nerZEQExw7">2600 1st Ave (on the corner of Vine), Seattle, WA 98121</a>.</p>
<p>In addition, AWS will host a <strong>Happy Hour</strong> (rooftop grill with beverages) on Saturday on the Amazon Nitro South building&rsquo;s 8th floor deck: <a href="https://goo.gl/maps/md5kWUHaNUGhR9JB7">2205 8th Ave, Seattle, WA 98121</a>.</p>
<h3 id="program">Program</h3>
<p><strong>All times are in PDT.</strong></p>
<h4 id="friday">Friday</h4>
<p><strong>Location:</strong> Hyatt Regency Bellevue on Seattle&rsquo;s Eastside, <strong>room Grand K</strong>, co-located with SIGMOD (900 Bellevue Way NE, Bellevue, WA 98004-4272)</p>
<table>
<thead>
<tr>
<th>start</th>
<th>finish</th>
<th>speaker</th>
<th>title</th>
</tr>
</thead>
<tbody>
<tr>
<td>08:30</td>
<td>08:45</td>
<td>Oskar van Rest (Oracle)</td>
<td>LDBC – State of the union – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/oskar-van-rest-ldbc-state-of-the-union.pdf">slides</a>, <a href="https://youtu.be/Frk7ITssaSY">video</a></td>
</tr>
<tr>
<td>08:50</td>
<td>09:05</td>
<td>Keith Hare (JCC / WG3)</td>
<td>An update on the GQL &amp; SQL/PGQ standards efforts – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/keith-hare-an-update-on-the-gql-and-sql-pgq-standards-efforts.pdf">slides</a>, <a href="https://youtu.be/LQYkal_0j6E">video</a></td>
</tr>
<tr>
<td>09:10</td>
<td>09:25</td>
<td>Stefan Plantikow (Neo4j / WG3)</td>
<td>GQL - Introduction to a new query language standard – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/stefan-plantikow-gql-v1.pdf">slides</a></td>
</tr>
<tr>
<td>09:30</td>
<td>09:45</td>
<td>Leonid Libkin (University of Edinburgh &amp; RelationalAI)</td>
<td>Formalizing GQL – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/leonid-libkin-formalizing-gql.pdf">slides</a>, <a href="https://youtu.be/YZE1a00h1I4">video</a></td>
</tr>
<tr>
<td>09:50</td>
<td>10:05</td>
<td>Semen Panenkov (JetBrains Research)</td>
<td>Mechanizing the GQL semantics in Coq – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/semyon-panenkov-gql-in-coq.pdf">slides</a>, <a href="https://youtu.be/5xBGohqWCzo">videos</a></td>
</tr>
<tr>
<td>10:10</td>
<td>10:25</td>
<td>Oskar van Rest (Oracle)</td>
<td>SQL Property Graphs in Oracle Database and Oracle Graph Server (PGX) – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/oskar-van-rest-sql-property-graphs-in-oracle-database-and-oracle-graph-server-pgx.pdf">slides</a>, <a href="https://youtu.be/owM9WiQubpg">video</a></td>
</tr>
<tr>
<td>10:30</td>
<td>11:00</td>
<td><em>coffee break</em></td>
<td></td>
</tr>
<tr>
<td>11:00</td>
<td>11:15</td>
<td>Alastair Green (JCC)</td>
<td>LDBC&rsquo;s organizational changes and fair use policies – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/alastair-green-ldbc-corporate-restructuring-and-fair-use-policies.pdf">slides</a></td>
</tr>
<tr>
<td>11:20</td>
<td>11:35</td>
<td>Ioana Manolescu (INRIA)</td>
<td>Integrating Connection Search in Graph Queries – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/ioana-manolescu-integrating-connection-search-in-graph-queries.pdf">slides</a>, <a href="https://youtu.be/LQPnmcrkUpY">video</a></td>
</tr>
<tr>
<td>11:40</td>
<td>11:55</td>
<td>Maciej Besta (ETH Zurich)</td>
<td>Neural Graph Databases with Graph Neural Networks – <a href="https://youtu.be/ce5qNievRNs">video</a></td>
</tr>
<tr>
<td>12:00</td>
<td>12:10</td>
<td>Longbin Lai (Alibaba Damo Academy)</td>
<td>To Revisit Benchmarking Graph Analytics – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/longbin-lai-benchmark-ldbc.pdf">slides</a>, <a href="https://youtu.be/s9Vtt-6t_FI">video</a></td>
</tr>
<tr>
<td>12:15</td>
<td>13:30</td>
<td><em>lunch</em></td>
<td></td>
</tr>
<tr>
<td>13:30</td>
<td>13:45</td>
<td>Yuanyuan Tian (Gray Systems Lab, Microsoft)</td>
<td>The World of Graph Databases from An Industry Perspective – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/yuanyuan-tian-world-of-graph-databases.pdf">slides</a>, <a href="https://youtu.be/AZuP_b95GPM">video</a></td>
</tr>
<tr>
<td>13:50</td>
<td>14:05</td>
<td>Alin Deutsch (UC San Diego &amp; TigerGraph)</td>
<td>TigerGraph&rsquo;s Parallel Computation Model – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/alin-deutsch-tigergraphs-computation-model.pdf">slides</a>, <a href="https://youtu.be/vcxdieJB80Y">video</a></td>
</tr>
<tr>
<td>14:10</td>
<td>14:25</td>
<td>Chen Zhang (CreateLink)</td>
<td>Applications of a Native Distributed Graph Database in the Financial Industry – <a href="https://youtu.be/GCCT79Sps9I">video</a></td>
</tr>
<tr>
<td>14:30</td>
<td>14:45</td>
<td>Ricky Sun (Ultipa)</td>
<td>Design of highly scalable graph database systems – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/ricky-sun-ultipa.pdf">slides</a>, <a href="https://youtu.be/Sg1F64O4vGM">video</a></td>
</tr>
<tr>
<td>14:50</td>
<td>15:30</td>
<td><em>coffee break</em></td>
<td></td>
</tr>
<tr>
<td>15:30</td>
<td>15:45</td>
<td>Heng Lin (Ant Group)</td>
<td>The LDBC SNB implementation in TuGraph – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/heng-lin-the-ldbc-snb-implementation-in-tugraph.pdf">slides</a>, <a href="https://youtu.be/fy8AuVerwnY">video</a></td>
</tr>
<tr>
<td>15:50</td>
<td>16:05</td>
<td>Shipeng Qi (Ant Group)</td>
<td>FinBench: The new LDBC benchmark targeting financial scenario – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/shipeng-qi-finbench.pdf">slides</a>, <a href="https://youtu.be/0xLZadDOfZk">video</a></td>
</tr>
<tr>
<td>16:10</td>
<td>17:00</td>
<td>host: Heng Lin (Ant Group), panelists: Longbin Lai (Alibaba Damo Academy), Ricky Sun (Ultipa), Gabor Szarnyas (CWI), Yuanyuan Tian (Gray Systems Lab, Microsoft)</td>
<td>FinBench panel – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/heng-lin-finbench-panel.pdf">slides</a></td>
</tr>
<tr>
<td>19:00</td>
<td>22:00</td>
<td><em>dinner</em></td>
<td><em><a href="https://www.blackbottleseattle.com/">Black Bottle gastrotavern</a> in Belltown: <a href="https://goo.gl/maps/hQzBRR2nerZEQExw7">2600 1st Ave (on the corner of Vine), Seattle, WA 98121</a></em></td>
</tr>
</tbody>
</table>
<h4 id="saturday">Saturday</h4>
<p><strong>Location:</strong> Amazon Nitro South building, <strong>room 03.204</strong> (<a href="https://goo.gl/maps/md5kWUHaNUGhR9JB7">2205 8th Ave, Seattle, WA 98121</a>)</p>
<table>
<thead>
<tr>
<th>start</th>
<th>finish</th>
<th>speaker</th>
<th>title</th>
</tr>
</thead>
<tbody>
<tr>
<td>09:00</td>
<td>09:45</td>
<td>Brad Bebee (AWS)</td>
<td>Customers don&rsquo;t want a graph database, so why are we still here? – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/brad-bebee-tuc-keynote.pdf">slides</a>, <a href="https://youtu.be/bJlkpDC--fM">video</a></td>
</tr>
<tr>
<td>10:00</td>
<td>10:15</td>
<td>Muhammad Attahir Jibril (TU Ilmenau)</td>
<td>Fast and Efficient Update Handling for Graph H2TAP – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/muhammad-attahir-jibril-fast-and-efficient-update-handling-for-graph-h2tap.pdf">slides</a>, <a href="https://youtu.be/e8ZAszBsXV0">video</a></td>
</tr>
<tr>
<td>10:20</td>
<td>11:00</td>
<td><em>coffee break</em></td>
<td></td>
</tr>
<tr>
<td>11:00</td>
<td>11:15</td>
<td>Gabor Szarnyas (CWI)</td>
<td>LDBC Social Network Benchmark and Graphalytics – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/gabor-szarnyas-ldbc-social-network-benchmark-and-graphalytics.pdf">slides</a></td>
</tr>
<tr>
<td>11:20</td>
<td>11:30</td>
<td>Atanas Kiryakov and Tomas Kovachev (Ontotext)</td>
<td>GraphDB – Benchmarking against LDBC SNB &amp; SPB – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/tomas-kovatchev-atanas-kiryakov-benchmarking-graphdb-with-snb-and-spb.pdf">slides</a>, <a href="https://youtu.be/U6OPpNFOWqg">video</a></td>
</tr>
<tr>
<td>11:35</td>
<td>11:50</td>
<td>Roi Lipman (Redis Labs)</td>
<td>Delta sparse matrices within RedisGraph – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/roi-lipman-delta-matrix.pdf">slides</a>, <a href="https://youtu.be/qfKsplV4Ihk">video</a></td>
</tr>
<tr>
<td>11:55</td>
<td>12:05</td>
<td>Rathijit Sen (Microsoft)</td>
<td>Microarchitectural Analysis of Graph BI Queries on RDBMS – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/rathijit-sen-microarchitectural-analysis.pdf">slides</a>, <a href="https://youtu.be/55B8CkH09js">video</a></td>
</tr>
<tr>
<td>12:10</td>
<td>13:30</td>
<td><em>lunch</em></td>
<td><em>on your own</em></td>
</tr>
<tr>
<td>13:30</td>
<td>13:45</td>
<td>Alastair Green (JCC)</td>
<td>LEX &ndash; LDBC Extended GQL Schema – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/alastair-green-lex.pdf">slides</a>, <a href="https://youtu.be/DVpeb4Ce9Uw">video</a></td>
</tr>
<tr>
<td>13:50</td>
<td>14:05</td>
<td>Ora Lassila (AWS)</td>
<td>Why limit yourself to {RDF, LPG} when you can do {RDF, LPG}, too – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/ora-lassila-why-limit-yourself-to-lpg-when-you-can-do-rdf-too.pdf">slides</a>, <a href="https://youtu.be/7uAInoUwdds">video</a></td>
</tr>
<tr>
<td>14:10</td>
<td>14:25</td>
<td>Jan Hidders (Birkbeck, University of London)</td>
<td>PG-Schema: a proposal for a schema language for property graphs – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/jan-hidders-pg-schema.pdf">slides</a>, <a href="https://youtu.be/yQNL8hBTE4M">video</a></td>
</tr>
<tr>
<td>14:30</td>
<td>14:45</td>
<td>Max de Marzi (RageDB and RelationalAI)</td>
<td>RageDB: Building a Graph Database in Anger – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/max-de-marzi-ragedb-building-a-graph-database-in-anger.pdf">slides</a>, <a href="https://youtu.be/LBbF8aslYFE">video</a></td>
</tr>
<tr>
<td>14:50</td>
<td>15:30</td>
<td><em>coffee break</em></td>
<td></td>
</tr>
<tr>
<td>15:30</td>
<td>15:45</td>
<td>Umit Catalyurek (AWS)</td>
<td>HPC Graph Analytics on the OneGraph Model – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/umit-catalyurek-onegraph-hpc.pdf">slides</a>, <a href="https://youtu.be/64tv5LA6Wr8">video</a></td>
</tr>
<tr>
<td>15:50</td>
<td>16:05</td>
<td>David J. Haglin (Trovares)</td>
<td>How LDBC impacts Trovares – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/david-haglin-trovares.pdf">slides</a>, <a href="">video</a></td>
</tr>
<tr>
<td>16:10</td>
<td>16:25</td>
<td>Wenyuan Yu (Alibaba Damo Academy)</td>
<td>GraphScope Flex: A Graph Computing Stack with LEGO-Like Modularity – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/wenyuan-yu-graphscope-flex.pdf">slides</a>, <a href="https://youtu.be/cRikoyDmMks">video</a></td>
</tr>
<tr>
<td>16:30</td>
<td>16:40</td>
<td>Scott McMillan (Carnegie Mellon University)</td>
<td>Graph processing using GraphBLAS – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/scott-mcmillan-graph-processing-using-graphblas.pdf">slides</a>, <a href="https://youtu.be/yb4hGBhUzQQ">video</a></td>
</tr>
<tr>
<td>16:45</td>
<td>16:55</td>
<td>Tim Mattson (Intel)</td>
<td>Graphs (GraphBLAS) and storage (TileDB) as Sparse Linear algebra – <a href="https://datasets.ldbcouncil.org/event/sixteenth-tuc-meeting/attachments/tim-mattson-graphblas-and-tiledb.pdf">slides</a></td>
</tr>
<tr>
<td>17:00</td>
<td>20:00</td>
<td><em>happy hour (rooftop grill with beverages)</em></td>
<td><em>on the Nitro South building&rsquo;s 8th floor deck</em></td>
</tr>
</tbody>
</table>
<h4 id="tuc-event-locations">TUC event locations</h4>
<p>A <a href="https://www.google.com/maps/d/u/0/edit?mid=19_fi4fV-3-PZkNWCCcmhU86ct2EZXbgo">map of the LDBC TUC events</a> we hosted so far.</p>
</description>
</item>
<item>
<title>LDBC SNB – Early 2023 updates</title>
<link>https://ldbcouncil.org/post/ldbc-snb-early-2023-updates/</link>
<pubDate>Wed, 15 Feb 2023 00:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/post/ldbc-snb-early-2023-updates/</guid>
<description><p>2023 has been an eventful year for us so far. Here is a summary of our recent activities.</p>
<ol>
<li>
<p>Our paper <a href="https://ldbcouncil.org/docs/papers/ldbc-snb-bi-vldb-2022.pdf">The LDBC Social Network Benchmark: Business Intelligence Workload</a> was published in PVLDB.</p>
</li>
<li>
<p>David Püroja just completed his MSc thesis on creating a design towards <a href="https://ldbcouncil.org/docs/papers/msc-thesis-david-puroja-snb-interactive-v2-2023.pdf">SNB Interactive v2</a> at CWI&rsquo;s Database Architectures group. David and I gave a deep-dive talk at the FOSDEM conference&rsquo;s graph developer room titled <a href="https://fosdem.org/2023/schedule/event/graph_ldbc/">The LDBC Social Network Benchmark</a> (<a href="https://www.youtube.com/watch?v=YNF6z6gtXY4">YouTube mirror</a>).</p>
</li>
<li>
<p>I gave a lightning talk at FOSDEM&rsquo;s HPC developer room titled <a href="https://www.youtube.com/watch?v=q26DHnQFw54">The LDBC Benchmark Suite</a> (<a href="https://www.youtube.com/watch?v=q26DHnQFw54">YouTube mirror</a>).</p>
</li>
<li>
<p>Our auditors have successfully benchmark a number of systems:</p>
<ul>
<li>SPB with the Ontotext GraphDB systems for the SF3 and SF5 data sets (auditor: Pjotr Scholtze)</li>
<li>SNB Interactive with the Ontotext GraphDB system for the SF30 data set (auditor: David Püroja)</li>
<li>SNB Interactive with the TuGraph system running in the Aliyun cloud for the SF30, SF100, and SF300 data sets (auditor: Márton Búr)</li>
</ul>
</li>
</ol>
<p>The results and the full disclosure reports are available under the <a href="https://ldbcouncil.org/benchmarks/spb/">SPB</a> and <a href="https://ldbcouncil.org/benchmarks/snb/">SNB benchmark pages</a>.</p>
</description>
</item>
<item>
<title>LDBC SNB Datagen – The winding path to SF100K</title>
<link>https://ldbcouncil.org/post/ldbc-snb-datagen-the-winding-path-to-sf100k/</link>
<pubDate>Tue, 13 Sep 2022 00:00:00 +0000</pubDate>
<guid>https://ldbcouncil.org/post/ldbc-snb-datagen-the-winding-path-to-sf100k/</guid>
<description><p>LDBC SNB provides a data generator, which produces synthetic datasets, mimicking a social network’s activity during a period of time. Datagen is defined by the charasteristics of realism, scalability, determinism and usability. More than two years have elapsed since my <a href="https://ldbcouncil.org/post/speeding-up-ldbc-snb-datagen/">last technical update</a> on LDBC SNB Datagen, in which I discussed the reasons for moving the code to Apache Spark from the MapReduce-based Apache Hadoop implementation and the challenges I faced during the migration. Since then, we reached several goals such as we refactored the serializers to use Spark&rsquo;s high-level writers to support the popular Parquet data format and to enable running on spot nodes; brought back factor generation; implemented support for the novel BI benchmark; and optimized the runtime to generate SF30K on 20 i3.4xlarge machines on AWS.</p>
<h1 id="moving-to-sparksql">Moving to SparkSQL</h1>
<p>We planned to move parts of the code to SparkSQL, an optimized runtime framework for tabular data. We hypothesized that this would benefit us on multiple fronts: SparkSQL offers an efficient batch analytics runtime, with higher level abstractions that are simpler to understand and work with, and we could easily add support for serializing to Parquet based on SparkSQL&rsquo;s capabilites.</p>
<blockquote>
<p>Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. Spark SQL includes a cost-based optimizer, columnar storage, and code generation to make queries fast.</p>
</blockquote>
<p>Dealing with the dataset generator proved quite tricky, because it samples from various hand-written distributions and dictionaries, and contains complex domain logic, for which SparkSQL unsuitable. We assessed that the best thing we could do is wrap entire entity generation procedures in UDFs (user defined SQL functions). However, several of these generators return entity trees<sup id="fnref:1"><a href="#fn:1" class="footnote-ref" role="doc-noteref">1</a></sup>, which are spread across multiple tables by the serializer, and these would have needed to be split up. Further complicating matters, we would have also had to find a way to coordinate the inner random generators&rsquo; state between the UDFs to ensure deterministic execution. Weighing these and that we could not find much benefit in SparkSQL, we ultimately decided to leave entity generation as it is. We limited the SparkSQL refactor to the following areas:</p>
<ol>
<li>table manipulations related to shaping the output into the supported layouts and data types as set forth in the specification;</li>
<li>deriving the Interactive and BI datasets;</li>
<li>and generating the factor tables, which contain analytic information, such as population per country, number of friendships between city pairs, number of messages per day, etc., used by the substitution parameter generator to ensure predictable query runtimes.</li>
</ol>
<p>We refer to points (1.) and (2.) collectively as dataset transformation, while (3.) as factor generation. Initially, these had been part of the generator, extracted as part of this refactor, which resulted in cleaner, more maintainable design.</p>
<p><img src="datagen_df_0.png" alt="Datagen stages"></p>
<p>The diagram above shows the components on a high level. The generator outputs a dataset called IR (intermediate representation), which is immediately written to disk. Then, the IR is input to the dataset transformation and factor generation stages, which respectively generate the final dataset and the factor tables. We are aware that spitting out the IR adds considerable runtime overhead and doubles the disk requirements in the worst-case scenario, however, we found that there&rsquo;s no simple way to avoid
it, as the generator produces entity trees, which are incompatible with the flat, tabular, column oriented layout of SparkSQL. On the positive side, this design enables us to reuse the generator output for multiple transformations and add new factor tables without regenerating the data.</p>
<p>I&rsquo;ll skip describing the social network graph dataset generator (i.e. stage 1) in any more detail, apart from its serializer, as that was the only part involved in the current refactor. If you are interested in more details, you may look up the <a href="https://ldbcouncil.org/post/speeding-up-ldbc-snb-datagen/">previous blogpost in the series</a> or the <a href="https://arxiv.org/abs/2001.02299">Interactive benchmark specification</a>.</p>