AI · alternatives · 2026
24 alternatives to Embeddinghub: A vector database built for Machine Learning embeddings
The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
Embeddinghub is a vector database designed to store and manage machine learning embeddings. Built for developers and data scientists working with AI models, it provides a specialized system for handling… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. Embeddinghub: A vector database built for Machine Learning embeddings launched in 2021; newer entries below may have overtaken it.
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The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
2022 · github.com · its alternatives →
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Supabase Vector▲398The open source backend for AI applications
2023 · supabase.com · its alternatives →
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End-to-end deep dive of the project, spanning a large GPU cluster, distributed RocksDB, and terabytes of sharded HNSW.
2025 · blog.wilsonl.in · its alternatives →
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Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
2025 · github.com · its alternatives →
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Improved vector search with open-source AI embeddings editor
2023 · its alternatives →
- 8VY
2025 · vectorvfs.readthedocs.io · its alternatives →
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Google EmbeddingGemma 2free▲318An open, lightweight multimodal embedding model
15d ago · blog.google · its alternatives →
- 10MD
2023 · louisquissetlabs.com · its alternatives →
- 11IM
As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
2024 · papermatch.mitanshu.tech · its alternatives →
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🦉⚡️Serverless, distributed vector database as an API - TimeSurgeLabs/athenadb
2024 · github.com · its alternatives →
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Embedding Atlas▲150Hey HN, we're happy to release Mycelium, a JavaScript library for creating graph visualizations of machine learning models or any other directed acyclic graphs. Mycelium powers the graph viewer of the Talaria [0] a research model visualization and optimization system, which was used to optimize the efficiency of Apple Foundation Models [1]. Everything works entirely on the client-side in the browser — we provide a rudimentary ONNX loader out of the box, which you can try by dragging model files into our website. It is also simple to define loaders for your own model formats. The library was…
2025 · apple.github.io · its alternatives →
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Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com · its alternatives →
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Hey HN We've just released the initial version of our open-source vector embedding pipeline. It's designed to embed large volumes of data. While embedding a few documents for Q&A is straightforward, consistently ingesting gigabytes of unstructured data is a whole different ballgame. By using our API, you can embed raw data and store vectors in your vector database, sidestepping the complexities of cloud infrastructure. Now, in true YC spirit, we're launching before everything is polished. Our Github repo (https://github.com/dgarnitz/vectorflow ) is a work in progress, and…
2023 · github.com · its alternatives →
- 17NN
Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up…
2021 · its alternatives →
- 18VD
Discover, evaluate, and access relevant embeddings in your go-to framework. Skip all the infra for scraping, cleaning, indexing, and updating high-quality embeddings.
2023 · embedding.store · its alternatives →
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DeepFace is a leading open-source library for facial recognition and facial attribute analysis, and the de facto standard in Python. It wraps multiple state-of-the-art models that have reached — and even surpassed — human-level accuracy in recognizing faces. By the numbers (as of early 2025): 15,000+ stars on GitHub; ~4 million installations via pip; 800+ citations in academic papers Whether you're building a cutting-edge AI project or simply exploring facial recognition, DeepFace makes advanced capabilities accessible with just a few lines of code.
2025 · github.com · its alternatives →
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Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…
2023 · github.com · its alternatives →
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2018 · wikipedia2vec.github.io · its alternatives →
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Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →