DataBridge - An open-source, modular, multi-modal RAG solution
For the past few weeks, I've been working on DataBridge, an open-source solution for easy data ingestion and querying. We support text, PDFs, images, and as of recently, we've added a video parser that can analyze and work well over frames and audio. We are also adding object tracking to improve video ingestion and context, and plan to do this for various data types. To get started, you can find the installation section in our docs at https://databridge.gitbook.io/databridge-docs/getting-starte.... There are a bunch of other useful functions and examples available there.…
DataBridge - An open-source, modular, multi-modal RAG solution launched on December 29, 2024 with 5 votes and more than 50% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
Open-source multimodal retrieval engine (Morphik Core). By Morphik — AI back office for skilled nursing & senior living (morphik.ai). - morphik-org/morphik-core
In the maker’s words, at launch
For the past few weeks, I've been working on DataBridge, an open-source solution for easy data ingestion and querying. We support text, PDFs, images, and as of recently, we've added a video parser that can analyze and work well over frames and audio. We are also adding object tracking to improve video ingestion and…
Does a similar job
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I built an offline open-source RAG system DataBridge2025 · github.com · ▲7Hey HN! Over the past few weeks, I’ve been working on DataBridge, an open-source solution for data ingestion and querying across text, PDFs, images, and videos. In our latest update, we’ve added a fully local deployment option: - No internet required – Runs entirely offline. - Customizable Models – Supports any LLM and embedding model via Ollama (with options for any other private providers) - Extensibility – You can plug in your own models or tools easily. This local-first approach ensures better privacy, security, and flexibility, especially for teams dealing with sensitive data. You can…
DataBridge2024 · databridge.gitbook.io · ▲10Simplify ingestion & querying of multimodal data for AI apps
FastGraphRAG – Better RAG using good old PageRank2024 · github.com · ▲457Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
Streamdal – an open-source tail -f for your data2023 · github.com · ▲148Hey there! This is Dan and Ustin (@uzarubin), and we want to share something cool we've been working on for the past year - an open-source `tail -f` for your data, with a UI. We call it "Streamdal" which is a word salad for streaming systems (because we love them) and DAL or data access layer (because we’re nerds). Here's the repo: https://github.com/streamdal/streamdal Here's the site: https://streamdal.com And here's a live demo: https://demo.streamdal.com (github repo has an explanation of the demo) — — — THE PROBLEM We built this because the…
Multi-modal RAG with ColQwen in a single line of Code2025 · github.com · ▲5Hi HN, we're Arnav and Adi, and we're building DataBridge - a multi-modal database built from the ground up with AI use cases in mind. We recently launched support for ColPali-style image embeddings and late-interaction retrieval. We've implemented a hamming distance version of retrieval which helps this approach scale significantly more when compared with the regular late-interaction similarity scoring. These embeddings provide a significantly better retrieval accuracy, with ColQwen achieving around an 89% average score on the ViDoRe benchmark, compared to around 67% for traditional parsing…
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