Related Products
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About
Datanamic Data Generator is a powerful data generator that allows developers to easily populate databases with thousands of rows of meaningful and syntactically correct test data for database testing purposes. An empty database is not useful for making sure your application will work as designed. You need test data. Writing your own test data generators or scripts is time consuming. Datanamic Data Generator will help you. The tool can be used by DBAs, developers, or testers, who need sample data to test a database-driven application. Datanamic Data Generator makes database test data generation easy and painless. It reads your database and displays tables and columns with their data generation settings. Only a few simple entries are necessary to generate comprehensive (realistic) test data. The tool can be used to generate test data from scratch or from existing data.
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About
EMS Data Generator for MySQL is an impressive tool for generating test data to MySQL database tables with the possibility to save and edit scripts. The utility can help you to simulate the database production environment and allows you to populate several MySQL database tables with test data simultaneously, define tables and fields for generating data, set value ranges, generate MySQL char fields by mask, define lists of values manually or select them from SQL queries, set generation parameters for each field type and has many other features to generate MySQL test data in a simple and direct way. Data Generator for MySQL also provides a console application, which allows you to generate MySQL test data in one-touch by using generation templates.
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About
Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Companies looking for a realistic test data platform
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Audience
IT teams looking for a tool for generating test data to MySQL database tables
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Audience
Enterprises searching for a synthetic test data solution to model their applications and databases
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
€59 per month
Free Version
Free Trial
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Pricing
$60 per year
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationDatanamic
The Netherlands
www.datanamic.com/datagenerator/
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Company InformationEMS Software Development
Founded: 1993
Russia
www.sqlmanager.net/products/mysql/datagenerator
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Company InformationGenRocket
Founded: 2012
United States
www.genrocket.com/enterprise-features/
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Categories |
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Integrations
Amazon Web Services (AWS)
Ansible
Azure SQL Database
DXC Cloud
Eightfold.ai
FitNesse
Gatling Enterprise
GitEye
GitHub
JUnit
|
Integrations
Amazon Web Services (AWS)
Ansible
Azure SQL Database
DXC Cloud
Eightfold.ai
FitNesse
Gatling Enterprise
GitEye
GitHub
JUnit
|
Integrations
Amazon Web Services (AWS)
Ansible
Azure SQL Database
DXC Cloud
Eightfold.ai
FitNesse
Gatling Enterprise
GitEye
GitHub
JUnit
|
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