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EDBT 2027: International Conference on Extending Database Technology

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EDBT
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Submission Date:
2026-10-07 Due in 34 days
Notification Date:
2026-12-05
Conference Date:
2027-04-06
Location:
Lille, France
Years:
30
CCF: B   ICORE: B   QUALIS: A2   Viewed: 171289   Tracked: 114   Attend: 19

Conference Partner Index (CP-I)

73.1 / 100
Ranked #279 of 5,647 conferences · Top 5%

#14 of 336 in Data Mining & Databases

Academic recognition (35%)
92
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
92
Community attention (10%)
72
Public record completeness (15%)
35

Inputs used: Listed as CCF B, ICORE B, QUALIS A2 · Editions on record: 30 · Researchers following it here: 114 · Researchers who opened this page in the past 24 months: 30

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-03

Call For Papers

EDBT 2027 (International Conference on Extending Database Technology) is a CCF B / ICORE B / QUALIS A2 conference held in Lille, France on 2027-04-06. The paper submission deadline is 2026-10-07. Acceptance notifications are sent on 2026-12-05.

The annual International Conference on Extending Database Technology (EDBT) is a leading international forum for researchers, developers, and users to present and discuss cutting-edge ideas, and to exchange techniques, tools, and experiences related to data management. The conference invites submissions of original research contributions related to all aspects of data management. A list of specific topics of interest is provided below and is by no means exhaustive:: Data Infrastructure & Systems Architecture Cloud data management High-availability systems Data management on modern hardware Distributed and parallel data management Storage, indexing, and physical database design Middleware and workflow management Sustainable and energy-efficient data management Data Processing & Query Management Query processing and optimization techniques Concurrency control, recovery, and transaction management Complex event processing and data streams Benchmarking and performance evaluation Data Models, Integration & Quality Data models and semantics Data integration, heterogeneous data management Schema mapping, matching, and integration Data quality, data profiling, data preparation, and data cleaning Data lakes and data discovery Metadata management and standards Query languages Provenance Uncertain, probabilistic, and approximate data Data management and AI Machine learning methods for data and database tuning Data-intensive and data-driven systems for ML/AI Tabular foundation models and LLMs Natural language processing for databases Multi-modal data Data management for ML/AI models Specialized Data Types & Domains Data lakes Graph data Spatial and temporal data Sensor, IoT, and mobile data Text data, extraction, and information retrieval Unstructured data and multimedia data Scientific and statistical data Analytics, Intelligence & Discovery Data mining and knowledge discovery Data warehousing, large-scale analytics, and ETL tools Process mining Knowledge graphs and knowledge management Semantic web and social networks Governance, Ethics & Human Interaction Privacy, security, and access control Responsible data management and ethics Data economy, data markets, data sovereignty Crowdsourced and collaborative data management Human-data interaction Data visualization, exploration, and user interfaces Usability, automaticity, interpretability, and explainability of data systems
Last updated by Dou Sun on

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