Demo Data from EDBT 2026 / reviewers in the wild / expert
Shireesh Thota
dblp:166/8394
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Database system architecture and tuning · 50% Information retrieval · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › indexing
document indexing |
0.2 | 1 | 2015 | Schema-Agnostic Indexing with Azure DocumentDB · Proc. VLDB Endow. 2015 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Schema-Agnostic Indexing with Azure DocumentDBabstractAzure DocumentDB is Microsoft's multi-tenant distributed database service for managing JSON documents at Internet scale. DocumentDB is now generally available to Azure developers. In this paper, we describe the DocumentDB indexing subsystem. DocumentDB indexing enables automatic indexing of documents without requiring a schema or secondary indices. Uniquely, DocumentDB provides real-time consistent queries in the face of very high rates of document updates. As a multi-tenant service, DocumentDB is designed to operate within extremely frugal resource budgets while providing predictable performance and robust resource isolation to its tenants. This paper describes the DocumentDB capabilities, including document representation, query language, document indexing approach, core index support, and early production experiences. Dharma Shukla, Shireesh Thota, Karthik Raman 0002, Madhan Gajendran, Ankur Shah, Sergii Ziuzin, Krishnan Sundaram, Miguel Gonzalez Guajardo, Anna Wawrzyniak, Samer Boshra, Mohamed Nassar 0002, Michael Koltachev, Sudipta Sengupta, Justin J. Levandoski, David B. Lomet |
Proc. VLDB Endow. | 2 |