nowfound

AI · March 3, 2021

NN

NNext.net – A Firebase-like managed vector storage for ML applications

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…

NNext.net – A Firebase-like managed vector storage for ML applications launched on March 3, 2021 with 37 votes, #1,326 of 3,696 launches that month and more than 75% of that year's launches.

In plain words

NNext.net is a managed vector storage service designed for machine learning applications, offering a database where feature vectors and embeddings are first-class citizens. It eliminates the need for workarounds like storing vectors in SQL/NoSQL databases or Redis, providing native support for vector-based query operations such as nearest neighbor search. The platform serves ML engineers building applications including similarity search, recommendation systems, and duplicate detection.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

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…

Does a similar job

all alternatives →
  • Embeddinghub: A vector database built for Machine Learning embeddings2021 · github.com · ▲118

    The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform

  • Supabase Vector2023 · supabase.com · ▲398

    The open source backend for AI applications

  • HelixDB – Open-source vector-graph database for AI applications (Rust)2025 · github.com · ▲237

    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.…

  • Embeddinghub2021 · github.com · ▲118

    An open-source database for machine learning

  • HelixDB – A graph database built on object storageJun 2026 · github.com · ▲159

    Hey HN, it’s been just over a year since we launched HelixDB (https://news.ycombinator.com/item?id=43975423), a project a friend and I started in college. It’s an OLTP graph database built on object-storage, with native vector search and full-text search (FTS). Why graph, vector and FTS? Graph databases provide a natural cognitive model for data, vectors allow for a semantic understanding of the entities and relationships in the graph, and FTS provides more specific filtering. Many AI-driven applications attempt to combine all of these functionalities by stitching together…

  • AG
    A GPU-accelerated binary vector index2025 · rlafuente.com · ▲65

    This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.

More ai this month

the category →
  • Video model that turns script into viral social media videos

    AI · 18d ago · spira.ai

  • The browser where Claude Code and Codex work beside you

    AI · 17d ago · rill.love

  • Kolibri is Aleph Alpha

    AI · 19d ago · tej.as

  • Paintings by AI models: programs run through a simulation of oil paint.

    AI · 21d ago · stillwet.art

  • A real-time world model you can explore and change

    AI · 29d ago · world.pixverse.video

  • Hemory▲381

    Keep listening. Searchable memory for your AI agents.

    AI · 30d ago · hemory.com

Source: Show HN post ↗ · launch text quoted in part

Launched alongside, March 2021

the whole month →
  • Ghost 4.0▲1,100

    Newsletters, memberships, subscriptions - all in one place

    Dev tools · 2021 · ghost.org

  • Life & fun · 2021 · practical-go-lessons.com

  • OpenVC▲903

    2,200+ VC firms by thesis. Radically free and open. 🚀

    Dev tools · 2021 · openvc.app

  • Case studies on how companies got their first 1000 customers

    Growth · 2021 · first1000.co

  • Build performant, native and cross-platform desktop applications with native Svelte + powerful CSS-like styling.🚀 - nodegui/svelte-nodegui

    Life & fun · 2021 · github.com

  • Life & fun · 2021 · coderelay.io