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Nachiket Rao

dblp:411/5660 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

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.

Network and information security
1 paper
Privacy and data protection · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Databases, data mining, and information retrieval
1 paper
Distributed and cloud data management · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection › privacy-preserving computation
access pattern hiding
0.912025
OasisDB: An Oblivious and Scalable System for Relational Data · Proc. VLDB Endow. 2025
Distributed systems › distributed system architecture
multi-tier architecture
0.912025
OasisDB: An Oblivious and Scalable System for Relational Data · Proc. VLDB Endow. 2025

Methods — techniques the papers use, named apart from their topics

waffle · 2.6oblivious query processing · 2.6PathORAM · 2.6
YearPublicationVenuePosition
2025 OasisDB: An Oblivious and Scalable System for Relational Data
abstract
We present OasisDB, an oblivious and scalable RDBMS framework designed to securely manage relational data while protecting against access and volume pattern attacks. Inspired by plaintext RDBMSs, OasisDB leverages existing oblivious key value stores (KV-stores) as storage engines and securely scales them to enhance performance. Its novel multi-tier architecture allows for independent scaling of each tier while supporting multi-user environments without compromising privacy. We demonstrate OasisDB's flexibility by deploying it with two distinct oblivious KV-stores, PathORAM and Waffle, and show its capability to execute a variety of SQL queries, including point and range queries, joins, aggregations, and (limited) updates. Experimental evaluations on the Epinions dataset show that OasisDB scales linearly with the number of machines. When deployed with a plaintext KV-store, OasisDB introduces negligible overhead in its multi-tier architecture compared to a plaintext database, CockroachDB. We also compare OasisDB with ObliDB and Obliviator, two oblivious RDBMSs, highlighting its advantages with scalability and multi-user support.
Haseeb Ahmed, Nachiket Rao, Abdelkarim Kati, Florian Kerschbaum, Sujaya Maiyya
Proc. VLDB Endow.2