edrenova

Thanks for the shout-out! Co-founder of Neosync here - love seeing more tools in this space and pushing the envelope further. Good luck!

Yup agreed. We built an orchestration engine into Neosync for that reason. Can handles all of the reading/writing from DBs for you. Also can generate data from scratch (using LLMs or not).

Nice write up, mock data generation with LLMs is pretty tough. We spent time trying to do it across multiple tables and it always had issues. Whether you look at classical ML models like GANs or even LLMs, they struggle with producing a lot of data and respecting FKs, Constraints and other relationships.

Maybe some day, it gets better but for now, we've found that using a more traditional algorithmic approach is more consistent.

Transparency: founder of Neosync - open source data anonymization - github.com/nucleuscloud/neosync

Thanks for the question! Faker is useful but doesn't have a lot of features. For example, referential integrity, data orchestration or the ability to read/write to a db. So faker can work for simple API schemas but if you need something more robust for an entire database, then that's where we can help.

Thanks! Yeah we generally recommend not making your databases public and instead connecting to them using a bastion host. We support this at Neosync. Also, ideally, not connecting to a live DB and instead a snapshot or back up. A read replica could work as well but a snapshot is better.