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ARCADE: A Real-Time Data System for Hybrid and Continuous Query Processing across Diverse Data Modalities

arXiv 2509.19757 ↗First posted 24 Sep 2025cs.DB cs.AIcited by 0

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Abstract (arXiv)

The explosive growth of multimodal data - spanning text, image, video, spatial, and relational modalities, coupled with the need for real-time semantic search and retrieval over these data - has outpaced the capabilities of existing multimodal and real-time database systems, which either lack efficient ingestion and continuous query capability, or fall short in supporting expressive hybrid analytics. We introduce ARCADE, a real-time data system that efficiently supports high-throughput ingestion and expressive hybrid and continuous query processing across diverse data types. ARCADE introduces unified disk-based secondary index on LSM-based storage for vector, spatial, and text data modalities, a comprehensive cost-based query optimizer for hybrid queries, and an incremental materialized view framework for efficient continuous queries. Built on open-source RocksDB storage and MySQL query engine, ARCADE outperforms leading multimodal data systems by up to 7.4x on read-heavy and 1.4x on write-heavy workloads.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 50 references that are in the map. First posted on arXiv 24 Sep 2025.

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References · 7

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2016Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphscited by 861
  3. 2024NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Modelscited by 472
  4. 2023Improving Text Embeddings with Large Language Modelscited by 303
  5. 2021SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Searchcited by 35
  6. 2014AsterixDB: A Scalable, Open Source BDMScited by 4
  7. 2018LSM-based Storage Techniques: A Surveycited by 3

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