Oracle Database 23ai Data Modeling and Schema Design for JSON-Relational Duality
The Align > Refine > Design Series, by Steve Hoberman and industry experts
The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications.
Topics
About the Book
Oracle, the company, the products
JSON support in the Oracle Database
The JSON document model
Hierarchical structure in documents
Polymorphism
Fields with multiple data types
Multiple document types in the same collection
Schema evolution and versioning
JSON-relational duality
Relational tables
SQL/JSON
GraphQL
Data modeling and schema design
Audience
Introduction: About Data Models
Data model explanation
Three model characteristics
Precise
Minimal
Visuals
Three model components
Entities
Relationships
Attributes and keys
Three model levels
Business terms (Align)
Logical (Refine)
Domain-Driven Data Modeling
Physical (Design)
Three model perspectives, plus a new one
Relational
Dimensional
Query
JSON-relational duality
Chapter 1: Align
Purpose
Our animal shelter
Approach
Step 1: Ask the six strategic questions
Step 2: Identify and define the terms
Step 3: Capture the relationships
Step 4: Determine the visual
Step 5: Review and confirm
Three tips
Three takeaways
Chapter 2: Refine
Purpose
Approach
Step 1: Apply elicitation techniques
Analyze workloads
Quantify relationships
Step 2: Refine queries
Step 3: Capture attributes and relationships
Three tips
Three takeaways
Chapter 3: Design
Purpose
Approach
Step 1: Select database(s)
Step 2: Secret sauce
JSON-relational duality to the rescue
Duality – data is both Tables and JSON documents at the same time
SQL + NoSQL APIs
Only select what’s needed
Sharing values across documents and collections
Intra-document update control
Controlled schema flexibility
JSON Schema
Generated fields
Data partitioning
Built-in optimistic concurrency control without locking
Polymorphism
Replace the ORM
Online application changes
Vectors and AI search
Time travel
Automated data modeling
JSON collection tables
Three takeaways
Conclusion
JSON-Relational Duality is a new concept that combines aspects of relational databases and document databases in one combined data model. Read Oracle Database 23ai Data Modeling and Schema Design for JSON-Relational Duality if you are a data professional who needs to expand your modeling skills to include Oracle 23ai JSON-Relational Duality or a technologist who works with either relational or document databases and want to learn how to benefit from combining both models.
We cover the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Align is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Refine is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Design is about the technical requirements. That is, designing to accommodate our model’s unique software and hardware needs.
If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.
About Beda
Beda Hammerschmidt studied computer science and later earned a PhD in indexing XML data. He joined Oracle as a software developer in 2006. He initiated the support for JSON in Oracle and is co-author of the SQL/JSON standard. Beda is currently managing groups supporting semi-structured data in Oracle (JSON, XML, Full Text, etc).
About Pascal
Pascal Desmarets is the founder and CEO of Hackolade (https://hackolade.com), a data modeling tool for NoSQL databases, storage formats, REST APIs, and JSON in RDBMS. He is a pioneer in Polyglot Data Modeling, i.e. data modeling for polyglot data persistence and data exchanges. He is an advocate of Metadata-as-Code to make business sense of technical data structures.
About Steve
Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modeling. He has worked as a business intelligence and data management practitioner and trainer since 1990. He is the author of Data Modelers Workbench and Data Modeling Made Simple, the founder of the Design Challenges group and the inventor of the Data Model Scorecard®.
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