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cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
ChainifyDB: How to Blockchainify any Data Management System
Felix Martin Schuhknecht, Ankur Sharma, Jens Dittrich, Divya Agr · 2019-12-11 · via cs.DB updates on arXiv.org

Today's permissioned blockchain systems come in a stand-alone fashion and require the users to integrate yet another full-fledged transaction processing system into their already complex data management landscape. This seems odd as blockchains and traditional DBMSs share large parts of their processing stack. Thus, rather than replacing the established data systems altogether, we advocate to simply 'chainify' them with a blockchain layer on top. Unfortunately, this task is far more challenging than it sounds: As we want to build upon heterogeneous transaction processing systems, which potentially behave differently, we cannot rely on every organization to execute every transaction deterministically in the same way. Further, as these systems are already filled with data and being used by top-level applications, we also cannot rely on every organization being resilient against tampering with its local data. Therefore, in this work, we will drop these assumptions and introduce a powerful processing model that avoids them in the first place: The so-called Whatever-LedgerConsensus (WLC) model allows us to create a highly flexible permissioned blockchain layer coined ChainifyDB that (a) is centered around bullet-proof database technology, (b) makes even stronger guarantees than existing permissioned systems, (c) provides a sophisticated recovery mechanism, (d) has an up to 6x higher throughput than the permissioned blockchain system Fabric, and (e) can easily be integrated into an existing heterogeneous database landscape.