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VLDB

VLDB is an international research community and annual conference focused on database management systems, data mining, information retrieval, and related areas such as distributed computing, cloud computing, big data, and data science. It convenes researchers, practitioners, and vendors from institutions including IBM, Microsoft, Google, Amazon (company), Facebook, and universities such as Stanford University, Massachusetts Institute of Technology, University of California, Berkeley, Carnegie Mellon University, and University of Toronto. The community intersects with other venues and organizations like ACM SIGMOD, IEEE, SIGIR, KDD, and ICDE.

Overview

VLDB serves as a nexus for work on relational model, NoSQL, NewSQL, columnar storage, in-memory databases, and graph database systems. Participants include developers from Oracle Corporation, SAP SE, Teradata, Snowflake (company), Cloudera, and research groups at Princeton University, Harvard University, University of Washington, University of Pennsylvania, and University of Illinois Urbana-Champaign. Topics commonly discussed relate to technologies like Hadoop, Spark (software), MapReduce, Apache Cassandra, MongoDB, Redis, PostgreSQL, and MySQL.

The origins trace to gatherings of database pioneers and labs such as IBM Research, Bell Labs, DEC, Xerox PARC, and groups led by researchers at University College London, ETH Zurich, University of Cambridge, and University of California, San Diego. Early milestones parallel advances by figures affiliated with E. F. Codd, Jim Gray, Michael Stonebraker, Don Chamberlin, and Raymond Boyce. Over decades the conference evolved alongside projects like System R, Ingres, RDBMS, Teradata systems, Postgres, and the development of standards such as SQL and ODBC. Key events and locations have included meetings in cities like Bangalore, Athens, Vienna, Toronto, Hong Kong, and Zurich, and collaborations with institutions such as Indian Institute of Science, Tsinghua University, University of Sydney, and École Polytechnique Fédérale de Lausanne.

The conference is organized by the VLDB Endowment, a nonprofit that coordinates program committees, tutorials, and industrial exhibitions. Program chairs and committees often feature academics from Columbia University, Yale University, Cornell University, Duke University, Johns Hopkins University, and University of Michigan. Industry partners have included Intel, NVIDIA, ARM, Cisco Systems, Hitachi, Fujitsu, and Alibaba Group. VLDB cooperates with co-located events like SIGMOD Conference, ICML, NeurIPS, AAAI, and The Web Conference to bridge communities working on machine learning, artificial intelligence, natural language processing, and computer vision.

Research presented at VLDB spans transaction processing, concurrency control, distributed transactions, consensus algorithms such as Paxos and Raft, replication, sharding, query optimization, cost-based optimizers, indexing, B-tree and LSM-tree structures, data warehousing, OLAP, stream processing, complex event processing, temporal databases, spatial databases, privacy-preserving computation, homomorphic encryption, differential privacy, and federated learning. Contributions influenced standards and products from companies such as SAP SE, Oracle Corporation, Microsoft, Google, Amazon (company), and research labs like Microsoft Research, Google Research, and Facebook AI Research. The community also addresses societal and regulatory contexts involving institutions like European Commission, National Science Foundation, Defense Advanced Research Projects Agency, National Institutes of Health, and World Economic Forum.

Accepted papers appear in proceedings managed by the VLDB Endowment and are cited alongside articles in venues such as ACM Transactions on Database Systems, IEEE Transactions on Knowledge and Data Engineering, Communications of the ACM, Proceedings of the VLDB Endowment, and edited volumes from publishers like Springer, Elsevier, MIT Press, and Oxford University Press. Special issues and workshop papers are cross-listed with conferences including KDD, SIGMOD, ICDE, PODS, EDBT, UbiComp, and CHI. Influential demo and system papers have described systems related to Bigtable, Spanner, Dremel, Presto (SQL query engine), F1 (Google) and open-source projects such as Apache Hive, Apache HBase, Apache Hudi, and Apache Flink.

The VLDB community recognizes impact through awards like the VLDB 10-Year Best Paper Award, ICDE Influential Paper Award cross-citations, and prizes aligned with honors such as the ACM Turing Award, ACM Infosys Foundation Award, IEEE John von Neumann Medal, and discipline-specific accolades at ACM SIGMOD and SIGKDD. Notable awardees have connections to laureates and researchers at Bell Labs, IBM Research, Microsoft Research, Stanford University, Massachusetts Institute of Technology, University of California, Berkeley, and ETH Zurich, whose work shaped database theory and practice including concepts like normalization (database), query processing, and transaction theory.