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Neosync icon

Neosync

Open source data anonymization and synthetic data orchestration for developers. Create high fidelity synthetic data and sync it across your environments.

Neosync screenshot 1

Cost / License

  • Freemium (Subscription)
  • Open Source

Platforms

  • Online
  • Self-Hosted
  • Software as a Service (SaaS)
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Features

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  1.  Ad-free
  2.  No Tracking
  3. Docker icon  Support for Docker
  4.  Kubernetes

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Neosync information

  • Developed by

    US flagNucleus Cloud Corp
  • Licensing

    Open Source and Freemium product.
  • Pricing

    Subscription that costs $0 per month + free version with limited functionality.
  • Written in

  • Alternatives

    4 alternatives listed
  • Supported Languages

    • English

AlternativeTo Category

Development

GitHub repository

  •  4,145 Stars
  •  223 Forks
  •  68 Open Issues
  •   Updated  (Archived)
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Neosync was added to AlternativeTo by Paul on and this page was last updated .
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What is Neosync?

Neosync is an open-source, developer-first way to anonymize PII, generate synthetic data and sync environments for better testing, debugging and developer experience.

Companies use Neosync to:

  • Safely test code against production data - Anonymize sensitive production data in order to safely use it locally for a better testing and developer experience
  • Easily reproduce production bugs locally - Anonymize and subset production data to get a safe, representative data set that you can use to locally reproduce production bugs quickly and efficiently
  • Fix broken staging environments - Catch bugs before they hit production when you hydrate your staging and QA environments with production-like data
  • Reduce your compliance scope - Use anonymized and synthetic data to reduce your compliance scope and easily comply with laws like HIPAA, GDPR, and DPDP
  • Seed development databases - Easily seed development databases with synthetic data for unit testing, demos and more

Features:

  • Generate synthetic data based on your schema
  • Anonymize existing production-data for a better developer experience
  • Subset your production database for local and CI testing using any SQL query
  • Complete async pipeline that automatically handles job retries, failures and playback using an event-sourcing model
  • Referential integrity for your data automatically
  • Declarative, GitOps based configs as a step in your CI pipeline to hydrate your CI DB
  • Pre-built data transformers for all major data types
  • Custom data transformers using javascript or LLMs
  • Pre-built integrations with Postgres, Mysql, S3

Official Links