Oracle SQL Developer Data Modeler Description
Oracle SQL Developer Data Modeler is a complimentary graphical application designed to boost efficiency and streamline the process of data modeling. With this tool, users can effortlessly create, navigate, and modify various models, including logical, relational, physical, multi-dimensional, and data type models. The Data Modeler also offers capabilities for both forward and reverse engineering, while facilitating collaborative efforts through built-in source code management. It is versatile enough to be utilized in traditional setups as well as cloud-based environments. As part of the Oracle Database Tools suite, Oracle SQL Developer Data Modeler stands out as a comprehensive, independent product featuring a wide array of data and database modeling tools and utilities. Additional resources, including a general FAQ and other relevant materials, can be found on the Data Modeler homepage. This document aims to address some of the pricing-related inquiries that have emerged within the community, providing helpful insights for users navigating these questions.
Oracle SQL Developer Data Modeler Alternatives
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
Its Governed Control Model connects business meaning, data structures, transformation rules, dependencies, lineage and technical implementation in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated outputs can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, supported Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Because generated outputs are native Microsoft technology, no AnalyticsCreator runtime is required in production. Organisations retain ownership of the resulting implementation and can integrate generated assets into Git, Azure DevOps and CI/CD workflows.
Lineage, documentation and dependency information remain connected to the design, helping teams understand change impact before regenerating affected assets.
Design Intelligence extends this governed project context into AI-assisted data engineering by providing authorised AI tools and agents with structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery and repeatable data product engineering.
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DbVisualizer is a universal database client for anyone who works with data, from indie developers and startups to professional teams managing complex database environments, including developers, DBAs, analysts, and data engineers working across relational and NoSQL databases.
Key features:
- SQL editor with intelligent autocomplete, visual query builders, variables, and execution tools
- AI Assistant for answering questions, explaining errors, and analyzing code
- Git integration for managing SQL scripts and team collaboration
- Customizable layouts, key bindings, and UI themes
- Favorites for frequently used scripts and database objects
- Configurable security settings for organizational requirements
Connects via JDBC to MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, BigQuery, and more. Runs on Windows, macOS, and Linux.
Nearly 7 million downloads, with Pro users in 150 countries, scaling from solo projects to enterprise database management.
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Looker
Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.
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ER/Studio Data Architect
ER/Studio Data Architect is an enterprise data modeling solution that helps organizations design, document, and manage data architecture across modern platforms. It enables data architects and database professionals to create conceptual, logical, and physical data models that connect business meaning with technical implementation. By defining entities, relationships, and standards before systems are built, ER/Studio helps ensure consistent definitions, accurate reporting, and reliable analytics.
A core capability of ER/Studio Data Architect is logical data modeling, which defines business concepts independently of technology. Logical models act as a semantic foundation for the organization, helping teams align on the meaning of key entities such as customers, products, and transactions. This approach reduces ambiguity, prevents semantic drift across systems, and improves the reliability of analytics and AI initiatives.
The platform provides powerful forward and reverse engineering capabilities. Architects can generate database schemas from models or reverse engineer existing databases to document and analyze current structures. Schema compare and merge tools detect differences between versions and generate scripts to apply updates efficiently.
ER/Studio Data Architect supports major platforms including SQL Server, Oracle, PostgreSQL, Snowflake, Databricks, and JSON-based systems. Automation features such as macros, data lineage, and impact analysis help teams understand dependencies and reduce manual work. The platform also includes ERbert, an AI-powered data modeling assistant that can generate logical models from natural language prompts, accelerating model creation while maintaining structured data architecture.
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Pricing
Free Version:
Yes
Integrations
Company Details
Company:
Oracle
Year Founded:
1977
Headquarters:
United States
Website:
www.oracle.com/in/database/technologies/appdev/datamodeler.html
Media
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Product Details
Platforms
Web-Based
Windows
Mac
Linux
Types of Training
Training Docs
Live Training (Online)
Webinars
In Person
Training Videos
Customer Support
Business Hours
Online Support
Oracle SQL Developer Data Modeler Features and Options
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