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AI · alternatives · 2026

24 alternatives to Epsilla – Open-source vector database with low query latency

Hey HN! We are building Epsilla (https://github.com/epsilla-cloud/vectordb), an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. When do we need a vector database? For example, GPT-3.5 has a 16k context window limit. If we want to let it answer a question about a 300 page book, we cannot put the whole book content into the context. We have to choose the sections of the book that are most relevant to the question. Vector database is specialized at ranking and picking the most relevant content from a large pool…

Epsilla is an open-source, self-hostable vector database designed for semantic similarity search with optimized low query latency. It helps applications find the most relevant content from large document pools to feed… 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. Epsilla – Open-source vector database with low query latency launched in 2023; newer entries below may have overtaken it.

  1. 1

    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 →

  2. 2

    OctaneDB is an open-source vector database for Python that focuses on ultra-fast similarity search for high-dimensional data—perfect for AI/ML, semantic search, and large-scale document or embedding retrieval. What does it do? Store, index, and search millions of embeddings (text, images, etc.) with sub-millisecond query time. Supports in-memory and efficient HDF5 persistent storage. Integrates seamlessly with sentence-transformers for automatic text embedding. Key Features: 10x faster than Pinecone or ChromaDB for vector search and batch insertions. Advanced indexing: HNSW (approximate…

    2025 · github.com · its alternatives →

  3. 3IM

    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 →

  4. 4

    🦉⚡️Serverless, distributed vector database as an API - TimeSurgeLabs/athenadb

    2024 · github.com · its alternatives →

  5. 5LA

    We are excited to share Lantern! Lantern is a PostgreSQL vector database extension for building AI applications. Install and use our extension here: https://github.com/lanterndata/lantern We have the most complete feature set of all the PostgreSQL vector database extensions. Our database is built on top of usearch — a state of the art implementation of HNSW, the most scalable and performant algorithm for handling vector search. There’s three key metrics we track. CREATE INDEX time, SELECT throughput, and SELECT latency. We match or outperform pgvector and pg_embedding…

    2023 · docs.lantern.dev · its alternatives →

  6. 6
    SereneDBfree▲262

    Ultra-Fast Search & Analytics Database, Agentic AI ready

    Sep 2026 · serenedb.com · its alternatives →

  7. 7

    Contribute to Z-Gort/Reservoirs-Lab development by creating an account on GitHub.

    2024 · github.com · its alternatives →

  8. 8

    I built [VectorLiteDB (https://github.com/vectorlitedb/vectorlitedb) — a simple, embedded vector database that stores everything in a single file, just like SQLite. The problem: If you’re a developer building AI apps, you usually have two choices for vector search - Set up a server (e.g. Chroma, Weaviate) - Use a cloud service (e.g. Pinecone) That works for production, but it’s overkill when you just want to: - Quickly prototype with embeddings - Run offline without cloud dependencies - Keep your data portable in a single file The inspiration was *SQLite* during…

    2025 · github.com · its alternatives →

  9. 9VY
  10. 10CH

    Hi HN! We're thrilled to share CozoDB v0.6, a monumental update to our FOSS database, which already unifies relational and graph features. With the addition of vector search, CozoDB becomes an even better companion for LLMs like ChatGPT. This release introduces vector search using HNSW indices within Datalog, enabling seamless integration with powerful features such as ad-hoc joins, recursive Datalog, and classical whole-graph algorithms. This update significantly broadens CozoDB's capabilities. Check out the linked release note for an in-depth look at the new features, comparisons to other…

    2023 · docs.cozodb.org · its alternatives →

  11. 11

    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…

    Jun 2026 · github.com · its alternatives →

  12. 12

    One year ago I open-sourced my very first 'real' project and shared it here. I was a college student in my senior year and desperately looking for a job. At the time of sharing it i couldn't even afford a domain and naively let someone buy the one i had my eyes on lol. It's been a hell of a year with this blowing up, me moving to another country, and switching 2 jobs. In a year we somehow managed to hit 26k stars, grow a 1000+ person discord community, and support 37 languages. I couldn't be more grateful for the community that helped this grow, but now i don't know what direction to take…

    2025 · drawdb.app · its alternatives →

  13. 13

    Serverless vector database for AI and LLMs

    2024 · upstash.com · its alternatives →

  14. 14

    We've open-sourced our no-code ETL framework for Vector Data processing. The VectorETL framework allows Data & AI engineers seamlessly process data from multiple data sources (S3, MySQL, Postgres, Salesforce) to ALL MAJOR vector databases (Pinecone, Weaviate, Qdrant, Milvus etc.) using just a config file. We'd love to get your feedback!

    2024 · github.com · its alternatives →

  15. 15AG

    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.

    2025 · rlafuente.com · its alternatives →

  16. 16

    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 →

  17. 17

    Hi HN, I built VectorDBZ, a cross-platform desktop app for exploring and analyzing vector databases like Qdrant, Weaviate, Milvus, and ChromaDB. It lets you browse collections, inspect vectors and metadata, run similarity searches, and visualize embeddings without writing custom scripts. GitHub (downloads and issues): https://github.com/vectordbz/vectordbz Feedback welcome. If it’s useful, starring the repo helps keep me motivated. Thanks.

    Jan 2026 · github.com · its alternatives →

  18. 18

    The portable vector database for AI agents beyond the cloud

    Apr 2026 · actian.com · its alternatives →

  19. 19

    We have been using graph DBs more and more at work. I found them painful to work with locally and decided to try and build something better.

    Aug 2026 · github.com · its alternatives →

  20. 20

    I created a web page to compare different analytical databases (both self-managed and services, open-source and proprietary) on a realistic dataset. It contains 20+ databases, each with installation and data loading scripts. And they can be compared to each other on a set of 43 queries, by data load time or by storage size. There are switches to select different types of databases for comparison - for example, only MySQL compatible or PostgreSQL compatible. If you play with the switches, many interesting details will be uncovered. Full description:…

    2022 · benchmark.clickhouse.com · its alternatives →

  21. 21

    Client Side Vector Database. Contribute to 0xnyn/tinkerbird development by creating an account on GitHub.

    2024 · github.com · its alternatives →

  22. 22

    I recently found myself computing the similarity between lots of very high dimensional vectors (i.e., sentence embedding vectors from LLMs), and I wanted to try some more powerful measures of similarity/dependency than just Cosine similarity, which seems to be the default for everything nowadays because of its computational efficiency. There are many other more involved measures that can detect more subtle relationships, but the problem is that some of them are quite slow to compute, especially if you're trying to do it in Python. For my favorite measure of statistical dependency,…

    2023 · github.com · its alternatives →

  23. 23

    Hey hacker news, we launched a few weeks ago as a GPT-powered chatbot for developer docs, and quickly realized that the value of what we’re doing isn’t the chatbot itself. Rather, it’s the time we save developers by automating the extraction of data from their SaaS tools (Github, Zendesk, Salesforce, etc) and helping transform it to contextually relevant chunks that fit into GPT’s context window. A lot of companies are building prototypes with GPT right now and they’re all using some combination of Langchain/Llama Index + Weaviate/Pinecone + GPT3.5/GPT4 as their stack for…

    2023 · github.com · its alternatives →

  24. 24PV

    Search a 100,000-article ParqDB index directly in the browser with MiniLM, HTTP Range, Parquet, and WebAssembly.

    Aug 2026 · search.parqdb.io · its alternatives →

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