特色

Create database documentation

With Dataedo you can quickly generate documentation of your existing databases.   

Create Data Dictionary

Dataedo helps your team and organization to create and maintain Data Dictionary for existing databases.

Discover and document table relationships

Dataedo reads foreign keys form database schema to the repository and enables users to add missing relationships to the same model enabling complete and consistent view of data model.

Document stored procedures and functions

Dataedo reads stored procedures, functions and triggers and enables you to describe procedure body, each parameter and returned value separately and add custom metadata fields. It includes this documentation and script in exported documents.

Discover and document dependencies

Dataedo imports dependencies from the database and lets you browse and navigate dependent objects in user interface or exported documents.

Document cross-database dependencies

What makes Dataedo stand out from other tools is the ability to document cross-database dependencies and define cross-database table relationships.

系統需求

Dataedo Editor (client software) can be run in following operating systems with following requirements:

Windows

• Windows 7, Windows 8, Windows 10.
• NET 4.0 installed.
• Minimum 512MB of memory.
• Minimum 100MB of available hard-disk space.
• Segoe UI Light font (for PDF export).

Additionally, connection to Oracle DB requires an installed Oracle Client software (version 8.1.7 or higher).

Dataedo on Linux

There are two ways of running Dataedo on Linux machine:

1. Virtual Machine - you can install Windows in a virtual machine using VMware or similar software. This method provides the best compatibility, but you will have to run a copy of Windows in the background.
2. Wine - Wine is a compatibility layer that allows running Windows applications on Linux by mapping api calls to Linux equivalents. Note that Wine is Not an Emulator and it won’t allow running Dataedo on architectures that are not natively supported (other than i386 and x64).

Dataedo 32 bit has been tested and runs reasonably well on Wine, however installation requires some tricks. Dataedo 64 bit likely won’t work as long as .NET 4 is only installable in 32-bit wine prefixes.

Requirements

You will need several pieces of software:

• Dataedo 5.2 or newer. Earlier versions will not run, causing exception on startup
• Wine version 2.0. We have tested older Wine (1.6) and Dataedo was unstable.
• .NET framework 4.0 installed in Wine
• 32 bit Oracle Client, if you want to connect to Oracle DB

Dataedo on Mac

There are two ways of running Dataedo on a Mac:

1. Virtual Machine - you can install Windows in a virtual machine using VMware or similar software. This method provides the best compatibility, but you will have to run a copy of Windows in the background.
2. Wine - Wine is a compatibility layer that allows running Windows applications on Linux by mapping api calls to Linux equivalents. Note that Wine is Not an Emulator and it won’t allow running Dataedo on architectures that are not natively supported (other than i386 and am64).

Dataedo 32 bit has been tested and runs reasonably well on Wine, however installation requires some tricks. Dataedo 64 bit likely won’t work as long as .NET 4 is only installable in 32-bit wine prefixes.

Requirements

You will need several pieces of software:

• Dataedo 5.2 or newer. Earlier versions will not run, causing exception on startup.
• Wine version 2.0. We have tested older Wine (1.6) and Dataedo was unstable.
• XQuartz is required to render GUI.
• .NET framework 4.0.
• 32-bit Oracle Client software if you are going to connect to Oracle database.
• (Optional) Homebrew package manager - allows you to run most of the installation through terminal. You don't strictly need to use it, but it will make the installation easier.

目前支援的資料庫有：

• Microsoft SQL Server
• Microsoft Azure SQL Database
• Oracle
• MySQL
• MariaDB Server
• Amazon Aurora
• Google Cloud for MySQL

未來計畫支援的資料庫有：

• PostgreSQL
• Amazon Redshift
• Snowflake
• Azure SQL Data Warehouse