Synth

Synth

Synth is an innovative open-source data-as-code tool that streamlines the generation of consistent, anonymized test data via a user-friendly CLI workflow. It allows users to define data models through a declarative configuration language, facilitating the creation of accurate data for development, testing, and CI, while seamlessly integrating with both SQL and NoSQL databases.

Top Synth Alternatives

1

RNDGen

RNDGen is an intuitive random data generator designed to create tailored test data efficiently.

2

MDClone

MDClone revolutionizes healthcare data exploration with its ADAMS platform, empowering organizations to transform insights into improved patient outcomes and operational efficiencies.

3

Subsalt

Subsalt revolutionizes data access for enterprises by automating privacy compliance through advanced generative models.

4

Syntheticus

Syntheticus enables organizations to generate high-quality, compliant synthetic data at scale, addressing challenges such as access, bias, and privacy regulations.

5

Rendered.ai

Rendereda.ai provides a robust platform for data scientists and engineers to generate synthetic datasets tailored for machine learning and AI training.

6

Datomize

The AI-powered platform empowers data analysts and machine learning engineers to create precise analytical data sets that mimic real-world scenarios.

7

syntheticAIdata

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8

Rockfish Data

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9

OneView

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10

DataCebo Synthetic Data Vault (SDV)

It leverages various machine learning techniques, from classical statistical methods to deep learning, enabling users...

11

Mimic

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12

Sixpack

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13

KopiKat

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14

Aindo

It enables secure collaboration across teams and partners while protecting sensitive information...

15

Benerator

With its intuitive model-driven interface, users can easily generate realistic datasets while ensuring GDPR compliance...

Top Synth Features

  • Open-source data-as-code tool
  • Simple CLI workflow
  • Consistent data generation
  • Scalable data solutions
  • Anonymized production-like data
  • Customizable test data fixtures
  • Declarative configuration language
  • Import data from sources
  • Accurate data models creation
  • Semi-structured data support
  • Database agnostic compatibility
  • SQL and NoSQL integration
  • Thousands of semantic types
  • Sensitive data anonymization
  • Generate data storytelling
  • Constraints and relations specification
  • Seed development environments
  • Continuous integration support
  • Realistic data generation
  • User-friendly documentation.