# nucleuscloud/neosync

Open Source Data Security Platform for Developers to Monitor and Detect PII, Anonymize Production Data and Sync it across environments.

Repository: https://github.com/nucleuscloud/neosync
Canonical: https://ross.abutalabs.com/products/neosync
Homepage: https://www.neosync.dev
Language: Go
License: NOASSERTION
License Family: other
Topics: docker, golang, synthetic-data, benthos, etl, orchestration, testing, typescript, open-source, reactjs, self-hosted, kubernetes, nextjs, test-data-generator, fine-tuning, synthetic-data-generation, faker, mysql, postgresql
Archived: true
Last push: 2025-08-30T18:22:04+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 39, release rhythm 28, longevity 78
- inputs: {"age_days": 1105, "days_push": 368, "days_rel": 418, "gap_med": 1, "n_releases_24m": 82}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4142, forks 232 (observed 2026-08-28T04:08:36.312795+00:00)

## What it is
Neosync is an open-source data security platform that detects PII, anonymizes production data, and generates synthetic data to sync across environments. It is developer-first and self-hostable, built with Go and TypeScript, deployable via Docker and Kubernetes.

## Use cases
- anonymize production data for local testing
- generate synthetic test data for postgres and mysql
- detect PII in databases
- sync staging environments with safe production-like data
- reproduce production bugs locally with anonymized data
- create referentially intact data subsets
- seed developer environments with realistic fake data

## When to choose
- you need to test against production-like data without exposing PII
- you want referentially intact synthetic or anonymized data across environments
- you need a self-hosted data anonymization and subsetting pipeline

## When to avoid
- you need actively maintained software - the repo was acquired and is no longer maintained
- you only need simple static fixtures rather than database-aware anonymization
- you require a fully managed SaaS with vendor support

## Facets
- artifact type: application
- maturity: abandoned
- function: etl, data-generation, security, testing, workflow-automation, database
- domain: privacy, developer-tools, databases, security, self-hosted
- platform: self-hosted, go
- tags: data-anonymization, synthetic-data, pii-detection, test-data, data-subsetting, faker, postgres, mysql, data-engineering, docker, kubernetes, typescript, web-server

## Member repositories
- nucleuscloud/neosync (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:36.312795+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:22:58.452714+00:00, confidence not recorded.
  - readme: https://github.com/nucleuscloud/neosync (fetched 2026-08-28T04:08:36.312795+00:00, sha 534a1143d251)
- Data as of 2026-08-30T08:39:29.467469+00:00.