ActorDB: A Unified Database Model Integrating Single-Writer Actors, Incremental View Maintenance, and Zero-Trust Messaging

• URL: http://arxiv.org/abs/2509.25285v1
• Date: Mon, 29 Sep 2025 09:51:01 GMT
• Title: ActorDB: A Unified Database Model Integrating Single-Writer Actors, Incremental View Maintenance, and Zero-Trust Messaging
• Abstract summary: ActorDB is a novel database architecture that tightly integrates a single-writer actor model for writes, Incremental View Maintenance (IVM), and a zero-trust security model as a core component.<n>We argue that ActorDB can offer a more robust, secure, and developer-friendly platform compared to solutions that require manual integration of separate systems for actor persistence, stream processing, and security.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: This paper presents ActorDB ( Dekigoto ) , a novel database architecture that tightly integrates a single-writer actor model for writes, Incremental View Maintenance (IVM), and a zero-trust security model as a core component. The primary contribution of this work is the unification of these powerful but complex concepts into a single, cohesive system designed to reduce architectural complexity for developers of modern, data-intensive applications. We argue that by providing these capabilities out-of-the-box, ActorDB can offer a more robust, secure, and developer-friendly platform compared to solutions that require manual integration of separate systems for actor persistence, stream processing, and security. We present the core architecture, discuss the critical trade-offs in its design, and define the performance criteria for a Minimum Viable Product (MVP) to validate our approach.

Related papers

• Agentic Designer: Progressive Multi-Agent Collaboration for Structure-Aware Interior Layout Generation [84.5255199507027]
  Agentic Designer is a progressive framework that formulates structure-aware interior layout generation as an iterative and constraint-verified decision process.<n>By layout decomposing into modular stages of proposal, verification, synthesis and adjustment, the framework coordinates three specialized agents, a Generator, an Evaluator, and a Refiner.<n>This mechanism enforces stepwise geometric validation and correction before each placement is committed, thereby preventing error accumulation.
  arXiv  Detail & Related papers  (2026-07-23T02:46:11Z)
• The Model Is Not the Product: A Dual-Pillar Architecture for Local-First Psychological Coaching [51.56484100374058]
  This report introduces Psych LM, an iOS application that validates the thesis that, for such applications, the surrounding architecture is paramount.<n>Psych LM runs a local, on-device language model within a purpose-built, local-first runtime designed for behavioral and life-coaching applications.
  arXiv  Detail & Related papers  (2026-05-23T05:49:11Z)
• OpenCompass: A Universal Evaluation Platform for Large Language Models [62.59671563145442]
  General-purpose large language models (LLMs) have become a critical link in advancing technological development.<n>Mainstream benchmark datasets face challenges such as the diversity of task types, inconsistent evaluation criteria, and fragmentation of data and processing.<n>This paper proposes and open-source Open LLMs, a one-stop, scalable, and high-concurrency general-purpose evaluation platform.
  arXiv  Detail & Related papers  (2026-05-19T02:50:11Z)
• Benchmarking Requirement-to-Architecture Generation with Hybrid Evaluation [8.867061253116367]
  Large Language Models (LLMs) have demonstrated significant potential in automating software engineering tasks.<n> Generating software architecture designs from requirement documents is a crucial step in software development.<n>R2ABench is a novel benchmark comprising diverse real-world software projects paired with comprehensive Product Requirements Documents (PRDs) and expert-curated PlantUML reference diagrams.
  arXiv  Detail & Related papers  (2026-04-08T04:58:36Z)
• Architecture-Aware Multi-Design Generation for Repository-Level Feature Addition [53.50448142467294]
  RAIM is a multi-design and architecture-aware framework for repository-level feature addition.<n>It shifts away from linear patching by generating multiple diverse implementation designs.<n>Experiments on the NoCode-bench Verified dataset demonstrate that RAIM establishes a new state-of-the-art performance.
  arXiv  Detail & Related papers  (2026-03-02T12:50:40Z)
• OpenSage: Self-programming Agent Generation Engine [56.399761469404496]
  We propose OpenSage, the first agent development kit (ADK) to automatically create agents with self-generated topology and toolsets.<n>OpenSage offers effective functionality for agents to create and manage their own sub-agents and toolkits.<n>We believe OpenSage can pave the way for the next generation of agent development, shifting the focus from human-centered to AI-centered paradigms.
  arXiv  Detail & Related papers  (2026-02-18T21:16:29Z)
• Affordance Representation and Recognition for Autonomous Agents [64.39018305018904]
  This paper introduces a pattern language for world modeling from structured data.<n>The DOM Transduction Pattern addresses the challenge of web page complexity.<n>The Hypermedia Affordances Recognition Pattern enables the agent to dynamically enrich its world model.
  arXiv  Detail & Related papers  (2025-10-28T14:27:28Z)
• DynaQuery: A Self-Adapting Framework for Querying Structured and Multimodal Data [0.0]
  We present DynaQuery, a unified, self-adapting framework for querying unstructured data.<n>At the heart of DynaQuery lies the Introspection and Linking Engine (SILE), a novel systems primitive that elevates schema linking to a first-class query planning phase.<n>Our findings provide a validated architectural basis for developing natural language database interfaces that are robust, adaptable, and predictably consistent.
  arXiv  Detail & Related papers  (2025-10-20T19:02:35Z)
• HECATE: An ECS-based Framework for Teaching and Developing Multi-Agent Systems [0.038233569758620044]
  HECATE is built using the Entity-Component-System architectural pattern, leveraging data-oriented design to implement multiagent systems.<n>We present the framework's architecture, core components, and implementation approach, demonstrating how it supports different agent models.
  arXiv  Detail & Related papers  (2025-09-08T08:26:01Z)
• OneCAT: Decoder-Only Auto-Regressive Model for Unified Understanding and Generation [91.45421429922506]
  OneCAT is a unified multimodal model that seamlessly integrates understanding, generation, and editing.<n>Our framework eliminates the need for external components such as Vision Transformers (ViT) or vision tokenizer during inference.
  arXiv  Detail & Related papers  (2025-09-03T17:29:50Z)
• vMODB: Unifying event and data management for distributed asynchronous applications [1.9948490148513414]
  Event-driven architecture (EDA) has emerged as a crucial architectural pattern for scalable cloud applications.<n>We propose vMODB, a distributed framework that enables the implementation of highly consistent and scalable cloud applications.<n>Our experiments show that vMODB outperforms a widely adopted state-of-the-art competing framework that only offers eventual consistency by up to 3X.
  arXiv  Detail & Related papers  (2025-04-28T12:55:36Z)
• Designing and Implementing a Generator Framework for a SIMD Abstraction Library [53.84310825081338]
  We present TSLGen, a novel end-to-end framework for generating an SIMD abstraction library. We show that our framework is comparable to existing libraries, and we achieve the same performance results.
  arXiv  Detail & Related papers  (2024-07-26T13:25:38Z)
• Serving Deep Learning Model in Relational Databases [70.53282490832189]
  Serving deep learning (DL) models on relational data has become a critical requirement across diverse commercial and scientific domains. We highlight three pivotal paradigms: The state-of-the-art DL-centric architecture offloads DL computations to dedicated DL frameworks. The potential UDF-centric architecture encapsulates one or more tensor computations into User Defined Functions (UDFs) within the relational database management system (RDBMS)
  arXiv  Detail & Related papers  (2023-10-07T06:01:35Z)
• AnyDB: An Architecture-less DBMS for Any Workload [0.0]
  Instead of hard-baking an architectural model, such as a shared-nothing architecture, we aim for a new class of so-called architecture-lesss. Our initial results show that our architecture-less AnyDB can provide significant speed-ups across varying workloads.
  arXiv  Detail & Related papers  (2020-09-04T15:38:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.