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Vortex: A Stream-oriented Storage Engine For Big Data Analytics

Summary: Vortex is a stream-oriented storage engine in Google BigQuery for real-time analytics on continuous data. It supports both streaming and batch workloads, delivering petabyte-scale ingestion with sub-second freshness and low-latency queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6866
Venue
SIGMOD
Year
2024
Pagerank
5.2528121e-05
Overall Rank
9,555 | 34.45%
DOI
10.1145/3626246.3653396

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{edara_sigmod24,
        title = {{Vortex: A Stream-oriented Storage Engine For Big Data Analytics}},
        author = {Edara, Pavan and Forbes, Jonathan and Li, Bigang},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626246.3653396},
        url = {https://dl.acm.org/doi/10.1145/3626246.3653396},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,649 BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse 2024 SIGMOD 6.586622e-05
10,996 Scribe: How Meta transports terabytes per second in real time 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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