Hey everyone, my team is looking into using LangGraph for our AI agent workflows. We’re planning to go with their SaaS Cloud option on the Plus plan to get started quickly and deploy our solution.
We need to pull LangSmith tracing information into our own custom PostgreSQL database so we can build personalized analytics dashboards for our platform. From what I’ve read in their documentation, it seems like this requires the Hybrid setup which is only available on Enterprise pricing.
Is this accurate? Has anyone found alternative methods to extract data from the SaaS Cloud version or connect to an external PostgreSQL instance? Any suggestions would be really appreciated!
Hit this same wall when we looked at LangGraph Cloud last year. You’re right - direct database connections only work with Hybrid deployment, which means Enterprise pricing. But we found a decent workaround. We set up a scheduled job that pulls data through the LangSmith API and syncs it to our PostgreSQL every few hours. Not real-time, but worked great for our analytics dashboards. The REST API covers most tracing data you’d want - run details, metadata, performance metrics. Built a simple Python script with their SDK to handle extraction and transformation. Downside is you’re managing the pipeline yourself, but it saved us thousands vs upgrading to Enterprise just for database access.
totally agree! i’ve been exploring the api for similar stuff too. yeah, it’s a pain but way cheaper than enterprise. just watch out for rate limits when you’re pulling data!
Been there. The API approach works but turns into a nightmare when you need solid data sync and error handling.
We solved this with Latenode instead of coding from scratch. Built automated workflows that pull from LangSmith API on any schedule, transform data, and push directly to PostgreSQL.
Best part? All the edge cases work without code. Rate limits hit? Retry logic kicks in. API changes? Update the workflow in minutes. Sync fails? Get alerts and rollback automatically.
Went from weeks building a Python pipeline to everything running in hours. No server maintenance or deployment mess.
Latenode does the heavy lifting so you can focus on analytics dashboards. Way more reliable than managing sync scripts yourself.
Hit this exact problem 8 months ago during our LangGraph eval. The database connection limits on Plus are brutal.
We built a lightweight data pipeline with webhooks instead of constant polling. LangSmith has webhook support for certain events - way better than hammering their API.
Combined webhook triggers with daily API syncs for historical stuff. Cut our API calls by 70% and stayed under rate limits.
Webhooks catch new runs instantly, then we bulk-pull once daily to grab anything missed. Dumps everything into PostgreSQL and feeds our dashboards.
Took a week to build and test. Way cheaper than Enterprise and more flexible since we own the whole pipeline. Just nail the webhook auth and add retry logic for API calls.