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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
Marlin: Efficient Coordination for Autoscaling Cloud DBMS...
Wenjie Hu, Guanzhou Hu, Mahesh Balakrishnan, Xiangyao Yu · 2025-08-04 · via cs.DB updates on arXiv.org

Modern cloud databases are shifting from converged architectures to storage disaggregation, enabling independent scaling and billing of compute and storage. However, cloud databases still rely on external, converged coordination services (e.g., ZooKeeper) for their control planes. These services are effectively lightweight databases optimized for low-volume metadata. As the control plane scales in the cloud, this approach faces similar limitations as converged databases did before storage disaggregation: scalability bottlenecks, low cost efficiency, and increased operational burden. We propose to disaggregate the cluster coordination to achieve the same benefits that storage disaggregation brought to modern cloud DBMSs. We present Marlin, a cloud-native coordination mechanism that fully embraces storage disaggregation. Marlin eliminates the need for external coordination services by consolidating coordination functionality into the existing cloud-native database it manages. To achieve failover without an external coordination service, Marlin allows cross-node modifications on coordination states. To ensure data consistency, Marlin employs transactions to manage both coordination and application states and introduces MarlinCommit, an optimized commit protocol that ensures strong transactional guarantees even under cross-node modifications. Our evaluations demonstrate that Marlin improves cost efficiency by up to 4.4x and reduces reconfiguration duration by up to 4.9x compared to converged coordination solutions.