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title: Easy Embeddings Indexing Pipelines with Redpanda and Neon
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# Easy Embeddings Indexing Pipelines with Redpanda and Neon

**[Neon](https://daily.dev/sources/neontech)** · 3 min read · 0 upvotes · 0 comments

## Summary

A walkthrough for building a high-throughput, scalable embeddings indexing pipeline using Redpanda and Neon without writing any code. The pipeline uses Redpanda Connect (Kafka-compatible) as a streaming buffer, computes embeddings locally via Ollama, and stores them in Neon's serverless PostgreSQL database with pgvector for vector similarity search. The setup is configured entirely in YAML and is designed for RAG applications such as natural-language search over e-commerce invoices.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://neon.com/blog/easy-embeddings-indexing-pipelines-with-redpanda-and-neon>

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---

Tags: [#nlp](https://daily.dev/tags/nlp), [#rag](https://daily.dev/tags/rag), [#redpanda](https://daily.dev/tags/redpanda), [#pgvector](https://daily.dev/tags/pgvector)

[View this post on daily.dev](https://daily.dev/posts/easy-embeddings-indexing-pipelines-with-redpanda-and-neon-jgts5u0yj)

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