Launch HN: Ardent (YC P26) – Postgres sandboxes in seconds with zero migration (tryardent.com)
In the last two years coding agents have gotten dramatically more capable at handling complex engineering tasks. But without access to a realistic sandbox at the DB layer for testing, they ship garbage that can take down production databases. I spent over a year building an AI Data Engineer that failed for this exact reason. Evan spent the last 12 years in data engineering and hit this wall building agents at his last company.
Ardent was built to make it possible for coding agents to get near instant access to production-like sandboxes so they can test their work. To do this we write a replication stream out of the target DB, scaling with kafka onto a read replica with copy on write enabled and autoscaling compute (we currently prefer neon as a primary branching engine due to their implementation of these properties).
Our replication stream uses logical replication + ddl triggers to enable usage on any hosted postgres DB since most platforms do not allow physical replication which is traditionally used for creating replicas.
This provides a few primary benefits:
1. Does not require a platform migration to a DB provider like neon, allowing strong separation of production and development concerns. 2. Minimal impact on the production database while allowing clones to spin up in <6s, even at TB scale with copy-on-write
Security matters a lot with cloning production so we run a proxy layer to generate custom postgres URLs and route all connections to allow more granular access control to clones, prevent credential leak, and follow a split plane architecture to allow full data residency on your cloud through BYOC.
We also support anonymization through the ability to register SQL that runs on branches before they are returned. This has been used for PII redaction and branch modification.
Our goal is to make every data infrastructure platform “cloneable” in one place so agents can fully test the impact of their changes on production like data environments without risk.
Here's a demo of it: https://youtu.be/5S1kwPtiRU0
We’d love to understand how you work with coding agents on the DB and if you try Ardent (it's free to get started) what worked, what broke and what’s missing.
25 comments
[ 2.9 ms ] story [ 58.3 ms ] threadThere is still value in carefully testing on your prod DB, but for that you could just easily maintain a read replica. I don’t see the need for a SaaS here.
How does this compare to managing our own read-only replica with anonymized data?
https://github.com/xataio/xata
`CREATE DATABASE clankerdb TEMPLATE sourcedb STRATEGY=FILE_COPY;`.
But Ardent can be useful for many, because cloud providers uses heavily restricted Postgres. And many use Aurora, which doesn't event let configure the `log_line_prefix`.
Though if cloud providers add file_copy_method=CLONE compatible managed pg ...
ref: https://boringsql.com/posts/instant-database-clones/
We self-host DBLab since we had trouble getting Xata, Neon, and hosted DBLab configured.
thank you for using DBLab
Can you DM me, please? Really curious about your experience
It's called branch hooks and lets you register SQL to be run against the branch after it's created but before it's handed to you (or an agent)
So you can retain production shapes but manipulate the data however you want to make it safe
One note on the pricing: it would kind of bum me out to pay $250/month for $100/month in credit.
That feels like I'm losing $150/month.
But seems like this may be less about the absolute price but more about the way the 100/month of credit feels?
What do you think could be better? The intention of the 250/month scale tier was intended for companies scaling up that want BYOC for data residency etc. etc. and give them enough to test things internally without worrying about an overage bill before running it directly on prod but this might be able to be implemented better.
What Ardent does makes sense for a team setting where several agents/developers require their own environment before deploying code. But from a one-man-show founder’s perspective, the constraint is not about isolation but rather self-discipline.