PVLDB
@pvldb
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The Proceedings of the VLDB Endowment (PVLDB) RSS Feed: https://t.co/5wEKOfq2OD Bluesky: https://t.co/jULSIiQ5M3
Joined March 2017
Vol:18 No:12 → LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender System https://t.co/QTkcyYMmXg
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Vol:18 No:12 → TuskFlow: An Efficient Graph Database for Long-Running Transactions https://t.co/iu3hMvNQvf
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Vol:18 No:12 → MD-MVCC: Multi-version Concurrency Control for Schema Changes in Azure SQL Database https://t.co/g10WRtMFGG
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Vol:18 No:12 → Towards Principled, Practical Document Database Design https://t.co/hAVVtecj1Q
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Vol:18 No:12 → Scribe: How Meta transports zettabytes per day in real time https://t.co/SSTafmQQH1
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Vol:18 No:12 → SiriusBI: A Comprehensive LLM-powered Solution for Data Analytics in Business Intelligence https://t.co/q6AvnuIAP6
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Vol:18 No:12 → SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning https://t.co/w7Ac9OBGRw
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Vol:18 No:12 → Unlocking the Power of CI/CD for Data Pipelines in Distributed Data Warehouses https://t.co/aFmskNDMVW
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Vol:18 No:12 → veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System https://t.co/I7fLssu0fh
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Vol:18 No:12 → From FASTER to F2: Evolving Concurrent Key-Value Store Designs for Large Skewed Workloads https://t.co/r5CwOPKIBj
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Vol:18 No:12 → GaussDB-Vector: A Large-Scale Persistent Real-Time Vector Database for LLM Applications https://t.co/dHWuIWvQ91
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Vol:18 No:12 → Magnus: A Holistic Approach to Data Management for Large-Scale Machine Learning Workloads https://t.co/URmtA8WQ0t
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Vol:18 No:12 → DECK: Experiences on Delta Checkpointing for Industrial Recommendation Systems https://t.co/GIoJZnFCLJ
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Vol:18 No:12 → GRewriter: Practical Query Rewriting with Automatic Rule Set Expansion in GaussDB https://t.co/sfsbYeYEV1
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Vol:18 No:12 → FDBKeeper: Enabling Scalable Coordination Services for Metadata Management using Distributed Key-Value Databases https://t.co/ctOK4B2s5m
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Vol:18 No:12 → VSAG: An Optimized Search Framework for Graph-based Approximate Nearest Neighbor Search https://t.co/60LMGf1Qzg
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