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.
Discussion (17 Comments)Read Original on HackerNews
`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/
There 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.
I’m very confused as to the target market here
On the real world data impact I absolutely agree. We added something called "branch hooks" which essentially let you define SQL to run against the branch before it's returned
This lets you essentially anonymize and modify the branch to scrub unintended external side effects.
It's something that we're still working on though and trying to design the right abstractions around because we want to get that part right.
Neon does support copy on write branching natively and autoscaling compute but you make certain performance tradeoffs. A lot of the folks we've talked to that use RDS or Planetscale are reliant on things like query latencies supported by that platform's specific architecture but also want the ability to test on branches. We let you get the best of both worlds (branch but leave your DB where it is and freely choose your production environment based on prod concerns)
Supabase does have branching but they do not branch the data so you can't test any interactions that rely on the data. You can restore from backup as an option but this slows down based on data size since you're actually moving data as opposed to copy on write.
Longer term we want to be the place you branch all your data infra. So expanding to S3, Snowflake, MySQL etc.
For now though we're focusing on just postgres and getting it right!
How does this compare to managing our own read-only replica with anonymized data?
We'd let you instantly clone prod + user defined auto-anonymization so you can test writes. The architecture also somewhat takes the place of an existing read replica if you want to use it like that to make it more cost efficient.
Also since we're using copy on write for the clones they're incredibly storage efficient and the autoscaling compute helps minimize cost on clones by minimizing excess compute uptime
I mean, they said "read-only" ...
It's not uncommon (hex.ai, etc all do this, as do developers, MCP tools, etc). One thing we do at Ardent is enable obfuscated read replicas. We can strip PII in the replicas, so your agents are operating on realistic (but not sensitive) data. Moreover, they can do so in a way that doesn't impact your production database and is fast enough to wire into your CI/CD processes.
Jeremy is correct, though. The main risk/concern is primarily agents with write access. There are two high profile instances in the last year of agents dropping production databases (even when, in one case, after being given explicit instructions to never do such a thing). While read-replicas of a primary DB solve the "agents can't destroy things" problem, they don't solve things like testing schema migrations (in particular) or updates to the data.
Small enough company without suitable MoC and they've got a real chance of getting it.
> I'm much more worried about people who give full write access to their agents! But at least this solves that problem.
Yeah it goes without saying that write access would be crazy... But, it seems like people don't really care about the fact that they are just giving their private data to companies like Anthropic, OpenAI and Google.
> Branch anonymization Branches default to a full copy of your production data.
<-- This doesn't seem a safe default to me...
Perhaps a data policy should be required to be in place before a branch can be cloned... The default configuration giving the LLM full prod data access by default, is a bad standard to set, I think.
Hey, I put on my pants the same way you do: by having my staff hold them up while I jump into them.
> But, it seems like people don't really care about the fact that they are just giving their private data to companies like Anthropic/Open AI and Google.
This isn't quite as risky as it seems. All of them have a TOS that says if you pay them enough money they won't train on your data. But you're right that there are probably a lot of people who aren't on those plans sharing private data.
> > Branch anonymization Branches default to a full copy of your production data. > <-- This doesn't seem a safe default to me...
Agreed, and I'm sure it will cause trouble if you don't also bring along with the copies the internal controls around access logging.
But also, for smaller companies, this isn't an issue since they don't have SOC2 and the other compliance needs yet. So it's probably a sane starting place for Ardent at this time. Most small startups let everyone in the company access the full database anyway.
> Perhaps a data policy should be required to be in place before a branch can be cloned... The default configuration giving the LLM full prod data access by default, is a bad standard to set, I think.
Or at least an easy way to copy it from the database you're branching from.
https://github.com/xataio/xata