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Alternatives

Products that do what GalaxDB does

AI-native database: SQL + vector search + training exports

  1. 1

    The in-browser Postgres sandbox with AI assistance

    2024 · database.build

  2. 2LA

    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

  3. 3

    Build remarkable AI applications

    2024

  4. 4PA

    2024 · github.com

  5. 5

    The portable vector database for AI agents beyond the cloud

    Apr 2026 · actian.com

  6. 6HF
  7. 7HO

    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

  8. 8CH

    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

  9. 9EO

    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

  10. 10PE

    Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too. The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our…

    Mar 2026 · github.com

  11. 11PN
  12. 12SA

    Hi HN, We're Luke and Phillip, and we're building Spice.ai OSS - a lightweight, portable runtime, built in Rust and powered by Apache DataFusion to locally materialize, accelerate, and query data tables sourced from any database, data warehouse or data lake. Phillip and I first introduced Spice on Show HN in September 2021. Since then, we’ve been schooled and humbled in every way building 100TB+ data and ML systems for the https://spice.ai cloud platform. Along with our customers, we struggled with getting fast, low-latency, high-concurrency SQL query within a budget, accessing and…

    2024 · github.com

  13. 13NC

    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

  14. 14
    Myriade101

    Ask your data. See the SQL. Self-host in one command.

    2025

  15. 15

    Bring AI to your database

    2023

  16. 16
    SemaDB109

    No fuss vector database for AI

    2023

  17. 17SD

    SnapQL is an open-source desktop app (built with Electron) that lets you query your Postgres database using natural language. It’s schema-aware, so you don’t need to copy-paste your schema or write complex SQL by hand. Everything runs locally — your OpenAI API key, your data, and your queries — so it's secure and private. Just connect your DB, describe what you want, and SnapQL writes and runs the SQL for you.

    2025 · github.com

  18. 18IB
  19. 19DL

    2014 · databaselabs.io

  20. 20
    NexQL6

    AI-native Postgres tooling, All in VS Code

    Jul 2026 · nexql.astrx.dev

  21. 21OF

    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

  22. 22

    Turn your entire database into a context window for AI

    Jul 2026 · polygres.com

  23. 23AG

    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

  24. 24SC

    Hi HN, we’re Luke and Phillip, and we’re building Spice.ai OSS - a lightweight, portable data and AI engine and powered by Apache DataFusion & Ballista for SQL query, hybrid-search, and LLM-inference across disaggregated-storage used by enterprises like Barracuda Networks and Twilio. We first introduced Spice [1] on HN in 2021 and re-launched it on HN [2] in 2024 re-built from the ground up in Rust. Spice includes the concept of a Data Accelerator [3], which is a way to materialize data from disparate sources, such as other databases, in embedded databases like SQLite and DuckDB. Today we’re…

    Dec 2025 · spice.ai

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