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What is Tonic?

Tonic offers an automated approach to creating mock data that preserves key characteristics of sensitive datasets, which allows developers, data scientists, and sales teams to work efficiently while maintaining confidentiality. By mimicking your production data, Tonic generates de-identified, realistic, and secure datasets that are ideal for testing scenarios. The data is engineered to mirror your actual production datasets, ensuring that the same narrative can be conveyed during testing. With Tonic, users gain access to safe and practical datasets designed to replicate real-world data on a large scale. This tool not only generates data that looks like production data but also acts in a similar manner, enabling secure sharing across teams, organizations, and international borders. It incorporates features for detecting, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Additionally, Tonic actively protects sensitive data through features like automatic scanning, real-time alerts, de-identification processes, and mathematical guarantees of data privacy. It also provides advanced subsetting options compatible with a variety of database types. Furthermore, Tonic enhances collaboration, compliance, and data workflows while delivering a fully automated experience to boost productivity. With its extensive range of features, Tonic emerges as a vital solution for organizations navigating the complexities of data security and usability, ensuring they can handle sensitive information with confidence. This makes Tonic not just a tool, but a critical component in the modern data management landscape.

What is DTM Data Generator?

The test data generation engine is designed for speed and efficiency, boasting around 70 integrated functions along with an expression processor that empowers users to produce complex test data reflecting dependencies, internal structures, and relationships. Notably, this advanced tool autonomously inspects existing database schemas to pinpoint master-detail key relationships, all without needing any action from the user. In addition, the Value Library provides a rich array of predefined datasets covering various categories, such as names, countries, cities, streets, currencies, companies, industries, and departments. Features like Variables and Named Generators make it easy to share data generation attributes among similar columns, enhancing productivity. Moreover, the intelligent schema analyzer contributes to creating more realistic data without requiring additional changes to the project, while the "data by example" function simplifies the task of enhancing data authenticity with very little effort. Ultimately, this tool is distinguished by its intuitive interface, making the process of generating high-quality test data not only efficient but also accessible for users of varying expertise. Its combination of automation and rich features sets a new standard in test data generation.

Media

Media

Integrations Supported

MySQL
PostgreSQL
SQL Server
Amazon Aurora
Amazon Redshift
Apache Spark
Databricks
Google Cloud BigQuery
MongoDB
Oracle Database
Snowflake
Yellowbrick

Integrations Supported

MySQL
PostgreSQL
SQL Server
Firebird
IBM Db2
IBM Informix
InterBase

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Not specified

Company Facts

Organization Name

Tonic

Date Founded

2018

Company Location

United States

Company Website

www.tonic.ai/

Company Facts

Organization Name

DTM Data Generator

Company Website

sqledit.com/dg/

Categories and Features

Categories and Features

Test Data Management

Not specified

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