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STEED: An Analytical Database System for TrEE-structured Data

Summary: STEED learns a schema tree from tree-structured data to reduce storage and speed up field access. Optimizes storage layout, in-memory organization, and simple-path handling to deliver orders-of-magnitude faster analytics than JSON/Parquet-based systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11481
Venue
VLDB
Year
2017
Pagerank
4.7501876e-05
Overall Rank
7,348 | 48.94%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,702 JSON Tiles: Fast Analytics on Semi-Structured Data 2021 SIGMOD 5.9796907e-05
8,716 Native JSON Datatype Support: Maturing SQL and NoSQL convergence in Oracle Database 2020 VLDB 4.4569825e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
109 Dremel: Interactive Analysis of Web-Scale Datasets 2010 VLDB 0.00048217028
2,006 Sinew: A SQL System for Multi-Structured Data 2014 SIGMOD 9.8144532e-05
2,780 JSON Data Management – Supporting Schema-less Development in RDBMS 2014 SIGMOD 8.1307901e-05
6,675 Exploiting Common Patterns for Tree-Structured Data 2017 SIGMOD 4.9615691e-05
7,007 Closing the functional and Performance Gap between SQL and NoSQL 2016 SIGMOD 4.8606428e-05
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