EDBT 2026 Demo / reviewers in the wild / expert
Douglas McMahon
dblp:147/1173 · also Douglas Mcmahon
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3
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
3 papers |
Data models and query languages · 62% Database system architecture and tuning · 30% Indexing and storage engines · 8% |
Topics — the 5 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data models and query languages
schema-less data management |
0.4 | 2 | 2016 | Closing the functional and Performance Gap between SQL and NoSQL · SIGMOD Conference 2016 JSON data management: supporting schema-less development in RDBMS · SIGMOD Conference 2014 |
Data models and query languages
semistructured data |
0.4 | 1 | 2020 | Native JSON Datatype Support: Maturing SQL and NoSQL convergence in Oracle Database · Proc. VLDB Endow. 2020 |
Data models and query languages › semistructured data
JSON data model |
0.2 | 1 | 2014 | JSON data management: supporting schema-less development in RDBMS · SIGMOD Conference 2014 |
Data models and query languages › semistructured data
JSON |
0.1 | 1 | 2016 | Closing the functional and Performance Gap between SQL and NoSQL · SIGMOD Conference 2016 |
Data models and query languages › semistructured data
semi-structured data model |
0.1 | 1 | 2016 | Closing the functional and Performance Gap between SQL and NoSQL · SIGMOD Conference 2016 |
Methods — techniques the papers use, named apart from their topics
JSON path language · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Native JSON Datatype Support: Maturing SQL and NoSQL convergence in Oracle DatabaseabstractBoth RDBMS and NoSQL database vendors have added varying degrees of support for storing and processing JSON data. Some vendors store JSON directly as text while others add new JSON type systems backed by binary encoding formats. The latter option is increasingly popular as it enables richer type systems and efficient query processing. In this paper, we present our new native JSON datatype and how it is fully integrated with the Oracle Database ecosystem to transform Oracle Database into a mature platform for serving both SQL and NoSQL style access paradigms. We show how our uniquely designed Oracle Binary JSON format (OSON) is able to speed up both OLAP and OLTP workloads over JSON documents. Zhen Hua Liu, Beda Christoph Hammerschmidt, Douglas McMahon, Hui J. Chang, Joshua Spiegel, Alfonso Colunga Sosa, Srikrishnan Suresh, Geeta Arora, Vikas Arora |
Proc. VLDB Endow. | 3 |
| 2016 | Closing the functional and Performance Gap between SQL and NoSQLabstractOracle release 12cR1 supports JSON data management that enables users to store, index and query JSON data along with relational data. The integration of the JSON data model into the RDBMS allows a new paradigm of data management where data is storable, indexable and queryable without upfront schema definition. We call this new paradigm Flexible Schema Data Management (FSDM). In this paper, we present enhancements to Oracle's JSON data management in the upcoming 12cR2 release. We present JSON DataGuide, an auto-computed dynamic soft schema for JSON collections that closes the functional gap between the fixed-schema SQL world and the schema-less NoSQL world. We present a self-contained query friendly binary format for encoding JSON (OSON) to close the query performance gap between schema-encoded relational data and schema free JSON textual data. The addition of these new features makes the Oracle RDBMS well suited to both fixedschema SQL and flexible-schema NoSQL use cases, and allows users to freely mix the two paradigms in a single data management system. Zhen Hua Liu, Beda Christoph Hammerschmidt, Douglas McMahon, Hui J. Chang |
SIGMOD Conference | 3 |
| 2014 | JSON data management: supporting schema-less development in RDBMSabstractRelational Database Management Systems (RDBMS) have been very successful at managing structured data with well-defined schemas. Despite this, relational systems are generally not the first choice for management of data where schemas are not pre-defined or must be flexible in the face of variations and changes. Instead, No-SQL database systems supporting JSON are often selected to provide persistence to such applications. JSON is a light-weight and flexible semi-structured data format supporting constructs common in most programming languages. In this paper, we analyze the way in which requirements differ between management of relational data and management of JSON data. We present three architectural principles that facilitate a schema-less development style within an RDBMS so that RDBMS users can store, query, and index JSON data without requiring schemas. We show how these three principles can be applied to industry-leading RDBMS platforms, such as the Oracle RDBMS Server, with relatively little effort. Consequently, an RDBMS can unify the management of both relational data and JSON data in one platform and use SQL with an embedded JSON path language as a single declarative language to query both relational data and JSON data. This SQL/JSON approach offers significant benefits to application developers as they can use one product to manage both relational data and semi-structured flexible schema data. Zhen Hua Liu, Beda Christoph Hammerschmidt, Douglas McMahon |
SIGMOD Conference | 3 |