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VLDB Scraper

Under maintenance

Try for free

Scrape academic papers from VLDB (Very Large Data Bases) proceedings one of the top-tier venues in database research. Ideal for literature reviews, citation analysis, research trend tracking, and building academic datasets.

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Pay per usage

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Developer

Iyadh Khan

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VLDB Papers Scraper - Academic Research Data Extractor

An Apify Actor that scrapes academic papers from VLDB (Very Large Data Bases) proceedings — one of the top-tier venues in database research. Ideal for literature reviews, citation analysis, research trend tracking, and building academic datasets.

What it does

For each paper across the specified VLDB volumes, the scraper extracts:

Volume - PVLDB volume number
Year - Corresponding publication year(s)
Title - Paper title
Authors - Author names
Abstract - Paper abstract
PDF Link - Direct link to the PDF
Artifact Available - Whether the paper has associated artifacts
URL - Link to the paper page

Input

Field	Type	Description	Default
`volumes`	`string[]`	Select PVLDB volumes from a dropdown (Volume 1–20, 2008–present)	`["17", "18", "19"]`
`max_workers`	`integer`	Parallel Chrome instances (1–4). Use 1–2 for 4GB, 3–4 for 8GB+.	`2`

Available volumes

Volume	Year(s)
1	2008
2	2009
3	2010
4	2010–2011
5	2011–2012
6	2012–2013
7	2013–2014
8	2014–2015
9	2015–2016
10	2016–2017
11	2017–2018
12	2018–2019
13	2019–2020
14	2020–2021
15	2021–2022
16	2022–2023
17	2023–2024
18	2024–2025
19	2025–2026
20	2026–2027

Example input

{
    "volumes": ["17", "18", "19"],
    "max_workers": 2
}

Output

Results are stored in the default dataset. Each item has this structure:

{
    "volume": 18,
    "year": "2024–2025",
    "title": "Example Paper Title",
    "authors": "Author One, Author Two",
    "abstract": "This paper presents...",
    "pdfLink": "https://www.vldb.org/pvldb/vol18/example.pdf",
    "artifactAvailable": true,
    "url": "https://www.vldb.org/pvldb/vol18/paper/example"
}

How it works

Visits each selected VLDB volume index page and collects all paper links
Splits papers across parallel Chrome workers (configurable, 1–4)
Each worker scrapes its assigned papers using Selenium + BeautifulSoup
Pushes each paper's data to the Apify dataset

Getting started

On Apify platform

Go to the Actor's page on the Apify platform
Select the volumes you want to scrape and set concurrency
Click Start and wait for the run to finish
Download the results from the Dataset tab (JSON, CSV, Excel, etc.)

Local development

Requires Chrome/Chromium and Chromedriver installed locally.

$apify run

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