End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure
Summary: Advocates end-to-end declarative analytics via co-designed engines and cloud infra: a composite DB engine emits dataflow graphs whose operators declare inputs, outputs, and parallelism. The cloud consumes these graphs for placement, scaling, caching, and isolation, enabling elastic, data-dependent parallelism over heterogeneous data lakes and non‑relational workloads. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pinghe Li (ETH Zurich)
- 2. Tom Kuchler (ETH Zurich)
- 3. Marko Kabić (ETH Zurich)
- 4. Tobias Stocker (ETH Zurich)
- 5. Gustavo Alonso (ETH Zurich)
- 6. Ana Klimovic (ETH Zurich)
BibTeX Citation
@inproceedings{li_cidr26,
address = {Amsterdam, Netherlands},
series = {{CIDR} '26},
title = {{End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Li, Pinghe and Kuchler, Tom and Kabić, Marko and Stocker, Tobias and Alonso, Gustavo and Klimovic, Ana},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,037 | Future-Proof Data Systems | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 29 of 29 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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