Dev tools · alternatives · 2026

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Langchain's new member-A SQL+Vector database built on ClickHouse launched in 2023; newer entries below may have overtaken it.

1. 1
   MyScaleDB open-sourced: a SQL vector database to Build AI APPs with SQL▲12

   A @ClickHouse fork that supports high-performance vector search and full-text search. - myscale/MyScaleDB

   2024 · github.com · its alternatives →

2. 2
   HelixDB – Open-source vector-graph database for AI applications (Rust)▲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.…

   2025 · github.com · its alternatives →

3. 3
   Actian VectorAI DB▲203

   The portable vector database for AI agents beyond the cloud

   Apr 2026 · actian.com · its alternatives →

4. 4SA
   ShapedQL – A SQL engine for multi-stage ranking and RAG▲80

   Hi HN, I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning. We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem. To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic…

   Jan 2026 · playground.shaped.ai · its alternatives →

5. 5
   I built a vector database API on Cloudflare▲101

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

   2024 · github.com · its alternatives →

6. 6
   How we leapfrogged traditional vector based RAG with a 'language map'▲162

   TL;DR: Vector-based RAG performs poorly for many real-world applications like codebase chats, and you should consider 'language maps'. Part of our mission at Mutable.ai is to make it much easier for developers to build and understand software. One of the natural ways to do this is to create a codebase chat, that answer questions about your repo and help you build features. It might seem simple to plug in your codebase into a state-of-the-art LLM, but LLMs have two limitations that make human-level assistance with code difficult: 1. They currently have context windows that are too small to…

   2024 · twitter.com · its alternatives →

7. 7
   LatticeDB – Like SQLite but for graph databases▲190

   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 →

8. 8CH
   CozoDB, Hybrid Relational-Graph-Vector Database▲137

   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 →

9. 9VY
   VectorVFS, your filesystem as a vector database▲279

   2025 · vectorvfs.readthedocs.io · its alternatives →

10. 10IB
    I built a MySQL storage engine which is InnoDB compatible▲106

    upscaledb - a blazingly fast embedded key-value store with analytical functions

    2016 · upscaledb.com · its alternatives →

11. 11
    ShapedQL▲211

    The SQL engine for search, feeds, and AI agents

    Jan 2026 · its alternatives →

12. 12OA
    OtterTune – Automated Database Tuning Service for RDS MySQL/Postgres▲164

    Yo. OtterTune is a database optimization service. It uses machine learning to automatically tune your MySQL and Postgres configuration (i.e., RDS parameter groups) to improve performance and reduce costs. It does this by only looking at your database's runtime metrics (e.g., INNODB_METRICS, pg_stat_database, CloudWatch). We don't need to examine sensitive queries or user tables. We spun this project out of my research group at Carnegie Mellon University in 2020. This week we've announced that OtterTune is now available to the public. We are offering everyone a starter account to try it out…

    2021 · its alternatives →

13. 13
    Epsilla – Open-source vector database with low query latency▲111

    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…

    2023 · github.com · its alternatives →

14. 14
    I wrote a VectorDB in Go, built for Hackers, not Hyperscalers▲8

    A Vector Store written in Go - Supports hybrid retrieval over BM25, Flat, HNSW, IVF, PQ and IVFPQ Index with Quantization, Metadata Filtering, Reranking, Reciprocal Rank Fusion, Soft Deletes, Index Rebuilds and much much more - 0xnyn/comet

    2025 · github.com · its alternatives →

15. 15
    Vectorly▲92

    Get web data behind clicks, searches, user interactions

    Dec 2025 · inkbox.ai · its alternatives →

16. 16
    SemaDB▲109

    No fuss vector database for AI

    2023 · semafind.com · its alternatives →

17. 17
    TinkerBird – A Chrome-native vector database▲107

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

    2024 · github.com · its alternatives →

18. 18PV
    ParqDB – Vector search in the browser from Parquet over HTTP"▲26

    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 →

19. 19
    Superlinked – Vector Embeddings for Structured and Unstructured Data▲7

    Hi HN, I'm Daniel from Superlinked! We have built an open-source framework that improves vector search relevance and usefulness by combining structured metadata with unstructured data in your embeddings. We included self-hostable API server that sits between your data sources and vector database. Docs: https://docs.superlinked.com/ We're launching our cloud offering soon where you can use Superlinked to orchestrate high-performance retrieval for RAG, Search & Recommendation apps in your own cloud. Looking for feedback and happy to answer questions!

    2024 · github.com · its alternatives →

20. 20AV
    A vector database with semantic SQL-like filtering▲5

    Hi HN! It’s always bothered me that there’s no real equivalent of SQL WHERE for vector content. Filtering is one of the cornerstones of a modern database — but vector DBs only support either top-k sort, which is only useful for fuzzy search, or metadata filtering, which isn’t semantic. I’ve found myself wanting all the results matching my semantic query, not just k! Aside from data analysis, it's relevant if you’re trying to do any LLM reasoning: you don’t make good decisions or reach good conclusions by considering a small subset of information. So, we’ve designed a filtering primitive on…

    2023 · reviews.emberml.com · its alternatives →

21. 21
    VectorDBZ, a desktop GUI for vector databases▲13

    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 →

22. 22VA
    VectorAdmin – An open-source vector database management system▲6

    Hey HN, At Mintplex Labs are building developer tools for AI applications. One area we encountered frustration was the use of Vector Databases like Pinecone, Chroma, QDrant, or Weaviate to "unlock" long-term memory and contextual answers. It is nearly impossible to manage this data when in use for production. The craziest thing was how you cannot atomically CRUD any vectors in most of these vector databases. Let alone easily copy, clone, or migrate data or entire indexes without paying for re-embedding - among other things. With VectorAdmin you get a database level UI with the ability to…

    2023 · vectoradmin.com · its alternatives →

23. 23
    AGX – Open-Source Data Exploration for ClickHouse (The New Standard?)▲48

    Hey HN, We are excited to announce that we’ve open-sourced AGX, a fast and lightweight data explorer for ClickHouse. It is designed for developers and analysts who want to leverage SQL-native querying in an IDE-like environment. Here’s what makes AGX stand out: - Built on ClickHouse (accessible via embedded chdb or remote instance). - IDE-like user interface: features tabs, a Monaco editor, and a fast keyboard workflow. - Zero setup required: no infrastructure or complex dashboards to manage. - Ideal for exploring live blockchain data, while also flexible enough for general ClickHouse usage…

    2025 · github.com · its alternatives →

24. 24NN
    NNext.net – A Firebase-like managed vector storage for ML applications▲37

    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 →

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 →