Flow with FlorDB 🌻

LSH index for approximate set containment search

Unofficial! English original and Chinese translation of the paper.

Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture (accepted by PVLDB)

NETS:Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing

SQLite which supports Per-Page-Logging approach, published at VLDB 2015

Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing

PromSketch: Approximation-First Timeseries Query at Scale

DBSee represents the Teradata best practice beliefs that can be checked for programmatically. DBSee consists of a set of SQL scripts developed by VLDB that run against the Teradata data dictionary. Each script can be used to inform a user of the current state of their Teradata system.

2022 VLDB Summer School

Read the Paper

NETS:Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing

Blockchain and Database Related Paper/Researcher List

Erebus: Explaining the Outputs of Data Streaming Queries

A customized and efficient database tuning system [VLDB'22]

Matelda, an interactive system for multi-table error detection that combines automated error detection with human-in-the-loop refinement.