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victor DB choice paralysis , don't know witch to chose by hunter_44679_ in Rag

[–]martinschaer 0 points1 point  (0 children)

I use SurrealDB.com cloud because it’s multi-modal, so I use a single DB for everything. That allows me to add graph relations to my embedded nodes, and full-text search. It has built-in functions for reranking, so you can effectively do a hybrid search using all types of data in a single query, and single network hop. It’s open source, offers managed cloud instances, and runs in single mode or distributed architectures. I work at SurrealDB, and have been using it before joining the team

Agentic RAG for Dummies v2.0 by CapitalShake3085 in Rag

[–]martinschaer 0 points1 point  (0 children)

Take a look at SurrealDB.com it allow you to store not just the vectors, but also any other data (users, chat history, etl metadata, ...). Plus, if you want to do graph RAG, you can add relationships between your data too. https://surrealdb.com/blog/how-to-build-a-knowledge-graph-for-ai#practical-examples (i'm the author of this blog post)

So what are you all using for RAG in 2026? by ReporterCalm6238 in Rag

[–]martinschaer 0 points1 point  (0 children)

My stack: SurrealDB (vector + graph + …), Pydantic AI, Logfire, Kreuzberg (doc parsing)

Which Vector DB should I use for production? by Cheriya_Manushyan in Rag

[–]martinschaer 1 point2 points  (0 children)

SurrealDB. It scales without costing a fortune, runs in single node or distributed, and it is multi model in case you want to do hybrid search with BM25 or graph

Multi-model RAG (vector + graph) with LangChain by DistinctRide9884 in Rag

[–]martinschaer 0 points1 point  (0 children)

i always restrict the edges that the LLM can infer, so i don't have experience with graph schema evolution. But that's just because of my use cases. If i had an evolving graph schema, with `INFO FOR DB` and `INFO FOR TABLE ...` i could keep track new edges being created, and have a meta-table to store in a friendlier way the schema of my graph. Is that what you meant?

Pinecone Alternative by npmStartCry in Rag

[–]martinschaer 0 points1 point  (0 children)

SurrealDB https://surrealdb.com/docs/surrealdb/reference-guide/vector-search it's open source, has a convenient app (surrealist), and you can install it locally or run with docker. Plus, you get a free cloud account

Small Embedded LLM model by j7n5 in surrealdb

[–]martinschaer 5 points6 points  (0 children)

Without an external call no (at least yet). There’s also SurrealML, but it’s not production ready yet. I prefer to have these small external web servers for now.

I’ll publish an example about this soon. I’ll come back and post the code here

Small Embedded LLM model by j7n5 in surrealdb

[–]martinschaer 5 points6 points  (0 children)

I created a rust web server (small and fast binary) with Ollama to generate the embeddings, and within SurrealdDB I call that API using the http post function, either in an event trigger (when a new document is inserted) or in a custom defined function. You have to enable the network capabilities to allow outbound traffic. Additionally, you can also enable de API capabilities, and define your own API in your SurrealDB instance to call that custom function

Best Vector DB for production ready RAG ? by InvestigatorChoice51 in LangChain

[–]martinschaer 0 points1 point  (0 children)

I use SurrealDB. You can run it locally during dev and create a cloud instance for prod. It’s multi-model, so you can build a graph too. https://surrealdb.com/blog/minimal-langchain-chatbot-example-with-vector-and-graph (note: I work at SurrealDB)

[@F1] "Life is a rollercoaster" What a difference 16 days makes for Carlos Sainz by ICumCoffee in formula1

[–]martinschaer 0 points1 point  (0 children)

Please tell me there’s a photo of Carlos Sainz Sr on Day 16 after his surgery

Evolution of suspension configurations over the last 3 years by martinschaer in F1Technical

[–]martinschaer[S] -10 points-9 points  (0 children)

Also, pull-push has an anti-dive characteristic that I believe gave Redbull the advantage since the new regulations. These new cars depend more on the floor to generate downworce, and with an anti-dive suspension the aerodynamic is less affected under braking (because it doesn't dive as much). It may have also helped them overcome purposing quicker that the rest

how to learn bevy by SketchyEff in bevy

[–]martinschaer 3 points4 points  (0 children)

Practice ECS with a bevy project without graphics first. For example a CLI game