Features
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Standard
For Data
Modeling
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Professional
For Advanced Data
Modeling
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Enterprise
For Expert Data Modeling
& Documentation
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Visual data modeling
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Define tables, columns, relationships, keys, sequences, indexes, domains, views, procedures and triggers
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IDEF1X, Crow's Foot, Codasyl and Relational notations
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Auto-arrange tables in the diagram
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Advanced keys management
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Reflexive relationships
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Multiple diagrams
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Multiple projects management
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Syntax highlighting
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Diagram sizing
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12 A0
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12 A0
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12 A0
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Split and merge relationship
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Supported databases
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Oracle database
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Micosoft SQL Server
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MySQL
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MariaDB
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PostgreSQL
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SQLite
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Firebird
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Microsoft Azure SQL database
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Azure Synapse Dedicated SQL Pool
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Amazon Redshift
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Amazon RDS
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Forward/Reverse engineering
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Ability to manage connections
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SSL Secure connections (PostgreSQL and MySQL)
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SSH connection to a remote server using password authentication and public key authentication method
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Windows authentication method in MS SQL Server connection
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Model validation
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Generation of SQL/DDL script from data models
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Generation of databases from data models
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Support for Before and After scripts at both project and database table levels
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Import from local and remote databases(Reverse engineering)
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Version management
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Reporting
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Export model as an image
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Data model printing
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Model documentation settings
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Generating navigable model documentation in HTML format
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Generating model documentation in MS Word format
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Generating model documentation directly into Confluence
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Test data
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Validate a model using a database sandbox
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Data forms
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Data grids
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Test data generation
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Generate maximum 10 000 rows per table
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Generate unlimited rows per table
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Generative AI features ⓘ
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Automatically generate entity relationship diagrams (ERDs) from natural language inputs such as data model descriptions, user stories, or requirements, using the generative AI feature
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Use the generative AI feature to update an existing data model by auto-generating tables & relationships from descriptions, user stories, or requirements
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Advanced Metadata Query Assistant powered by ChatGPT API: Ask and get answers as reports and statistics from your data model
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Expert mode into the Advanced Metadata Query Assistant: See the SQL query extracted from the natural language question and the ability to fine-tune and edit the query as needed
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AI-Powered description generation for Procedures, Views, and Triggers
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Advanced tools
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Collaborative modeling with Git: Configure ERBuilder data modeler to work with Git. Browse different versions of the model from the repository, merge and compare with the local model
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Advanced exploration of a data model
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Advanced search in the data model browser
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Generate web user interface for CRUD applications
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Switch to another target database
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Compare model to model
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Compare model to database
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Compare database to database
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Generate compare HTML report
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Generate database/model synchronization script
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Update model from database
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Build an enterprise data dictionary automatically
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Generate data dictionary/documentation report using the ERBuilder command line
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Requirements management: Ability to create and assign requirements to tables, columns, constraints, triggers, procedures and relationships
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Document a database with user-defined metadata fields
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Other features
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Ability to find objects by name
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Global search and replace
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Replacing data type
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Treeview contextual menu
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Copy/Paste
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Undo/Redo
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Options management
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Reach objects from treeview
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Free Trial
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Free Trial
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Free Trial
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