Neosync

What it does

Neosync is an open source data platform that helps engineering teams anonymize production data and sync it across their environments so they can safely use it locally for testing code, detecting sensitive data in LLM prompts and generating synthetic data.

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  Neosync – Open-Source Data Anonymization for Postgres and MySQL2024 · github.com · ▲246

  Hey HN, we're Evis and Nick and we're excited to be launching Neosync (https://www.github.com/nucleuscloud/neosync). Neosync is an open source platform that helps developers anonymize production data, generate synthetic data and sync it across their environments for better testing, debugging and developer experience. Most developers and teams have some version of a database seed script that creates some mock data for their local and stage databases. The problem is that production data is messy and it’s very difficult to replicate that with mock data. This causes two big…

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  Open-Source Data Anonymization for Developers2024 · docs.neosync.dev · ▲13

  Hey HN, we're Evis and Nick from Neosync (https://www.github.com/nucleuscloud/neosync). Since we last introduced Neosync on HN 4 months ago, we’ve made a lot of progress and we’re excited to be launching several new features. As a reminder, Neosync is an open source platform that helps developers anonymize production data, generate synthetic data, subset it and sync it across their environments for better testing, debugging and developer experience. We do all of this while handling referential integrity. Whether you have primary keys, foreign keys, unique constraints,…

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  Open-Source Data Replication and Anonymization2023 · github.com · ▲24

  Hey HN, we're Evis and Nick, we're excited to be launching Neosync on HN! Neosync is an open source data replication and anonymization project that helps developers create safe, anonymized test data and sync it across all environments for high-quality local, stage and CI testing. This is how it works: 1. You select a job type. Today we support data sync jobs (these sync data between two databases and run on a schedule you define) and a data generation job (this generates synthetic data from scratch and sends it to a destination). 2. Next you define your source database and a destination(s)…

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