hmm, this is new and interesting So, is Postgres like a master wrapper around DuckDB and other transactional components? And do you also support embedding?
Congrats on the launch
Report
Maker
Hi @chilarai . Thanks for the feedback and attention!
Postgres is our foundation — every feature we build grows from it. Our goal is to provide out-of-the-box support for diverse use cases, including DuckDB-powered analytics, AI search (vector and full-text), and time-series workloads — all within one unified platform.
For embeddings, our current approach is to deliver one platform for the entire pipeline. You can use our OpenAPI to generate embeddings and then store them directly in the database.
Looking ahead, we plan to integrate embedding generation directly inside Postgres, so that RAG workflows become as simple as running an INSERT or SELECT query.
We really appreciate your input — community feedback helps us move faster and smarter. Thanks again, and feel free to reach out anytime!
We built Relyt ONE because we felt that working with data today often means stitching together too many systems—one for OLTP, one for analytics, one for full-text search, one for vectors—and the process gets heavy, complex, and costly.Â
Our goal was to make Postgres powerful enough to handle all of these workloads natively, while remaining familiar, lightweight, and instantly usable.Â
With built-in vector search, full-text search, and analytics (via pg_duckdb) all living inside the same Postgres environment, you can capture both operational data and semantic/analytical insights in one place, without extra infrastructure to manage. And because it’s serverless with instant spin-up, you can go from idea to running queries in seconds—whether you're prototyping a new AI-powered feature or scaling a production workload.Â
We hope this removes friction, reduces stack complexity, and simply makes building with data feel enjoyable again. Happy to answer questions and would love your feedback! 🙌
Swytchcode
hmm, this is new and interesting
So, is Postgres like a master wrapper around DuckDB and other transactional components?
And do you also support embedding?
Congrats on the launch
Hi @chilarai . Thanks for the feedback and attention!
Postgres is our foundation — every feature we build grows from it. Our goal is to provide out-of-the-box support for diverse use cases, including DuckDB-powered analytics, AI search (vector and full-text), and time-series workloads — all within one unified platform.
For embeddings, our current approach is to deliver one platform for the entire pipeline. You can use our OpenAPI to generate embeddings and then store them directly in the database.
Looking ahead, we plan to integrate embedding generation directly inside Postgres, so that RAG workflows become as simple as running an INSERT or SELECT query.
We really appreciate your input — community feedback helps us move faster and smarter.
Thanks again, and feel free to reach out anytime!
Swytchcode
@ywxiao Awesome. I would love to connect with you, but I don't have any way to reach out to you.
You can join our community on Discord. https://discord.gg/2v8hfEzKvW
Or feel free to reach out to me directly at ywxiaozero@gmail.com
Hey Product Hunt community!
We built Relyt ONE because we felt that working with data today often means stitching together too many systems—one for OLTP, one for analytics, one for full-text search, one for vectors—and the process gets heavy, complex, and costly.Â
Our goal was to make Postgres powerful enough to handle all of these workloads natively, while remaining familiar, lightweight, and instantly usable.Â
With built-in vector search, full-text search, and analytics (via pg_duckdb) all living inside the same Postgres environment, you can capture both operational data and semantic/analytical insights in one place, without extra infrastructure to manage. And because it’s serverless with instant spin-up, you can go from idea to running queries in seconds—whether you're prototyping a new AI-powered feature or scaling a production workload.Â
We hope this removes friction, reduces stack complexity, and simply makes building with data feel enjoyable again. Happy to answer questions and would love your feedback! 🙌
Try it now and tell us what your think:Â https://relytone.data.cloud/
Github:Â https://github.com/relytcloud
Docs:Â https://docs-relytone.data.cloud/
Join our Discord:Â https://discord.gg/2v8hfEzKvW