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What is Redgate SQL Data Generator?

Data can be swiftly generated using table names, column definitions, field sizes, data types, and other established parameters. These data generators are highly customizable to meet your individual requirements. In SQL Server Management Studio, significant volumes of data can be created with just a few clicks. The system supports column-specific data generation, allowing the value in one column to be influenced by another's content. Users gain increased flexibility and control when generating foreign key data, which is essential for relational databases. Additionally, custom generators can be shared with your colleagues, enabling the storage of regular expressions and SQL statement generators for team collaboration. You also have the option to create your own generators using Python, which allows you to generate any extra data that may be necessary. Using seeded random data generation ensures that the same dataset is consistently produced in every run. Furthermore, foreign key support plays a crucial role in preserving data integrity across different tables, enhancing both efficiency and reliability in the process. This adaptability in data generation not only simplifies workflows but also significantly boosts productivity in database management tasks, making it a valuable tool for developers and data analysts alike. With such capabilities, your data generation process becomes both innovative and seamless.

What is IBM InfoSphere Optim?

Proper management of data throughout its entire lifecycle is crucial for organizations to meet their business goals while reducing potential risks. Archiving data from outdated applications and historical transaction records is vital to ensure ongoing access for compliance inquiries and reporting purposes. By distributing data across different applications, databases, operating systems, and hardware, organizations can improve the security of their testing environments, accelerate release cycles, and decrease expenses. Failing to implement effective data archiving can lead to significant degradation in the performance of essential enterprise systems. Tackling data growth directly at its origin not only enhances efficiency but also minimizes the risks associated with long-term management of structured data. Moreover, it is important to protect unstructured data within testing, development, and analytics settings throughout the organization to preserve operational integrity. The lack of a solid data archiving strategy can severely impact the functionality of critical business systems and hinder overall success. Consequently, taking proactive measures to manage data effectively is fundamental for cultivating a more agile, resilient, and competitive enterprise in today's fast-paced business landscape.

Media

Media

Integrations Supported

IBM ILOG CPLEX Optimization Studio
IBM InfoSphere Optim Data Privacy
SQL Server

Integrations Supported

IBM ILOG CPLEX Optimization Studio
IBM InfoSphere Optim Data Privacy
SQL Server

API Availability

Has API

API Availability

Has API

Pricing Information

$405 per user per year
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Redgate Software

Date Founded

1999

Company Location

United Kingdom

Company Website

www.red-gate.com/products/sql-development/sql-data-generator/

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/analytics/optim

Categories and Features

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

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