NodeDB
High Perfomance Multi-Model Database
Details
- External ID
- 48102084
- Source
- HN
- Company
- —
- Product
- NodeDB
- Website domain
- github.com
- Launched
- May 11, 2026
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.1147011308562197
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
Hey HN,I've been working on a multi-model database called NodeDB.Originally, i've found out the idea of SurrealDB quite good. However, it doesn't have some graph and vector features that I need. And since it is just a KV wrapper, instead of purpose-built engine, the performance will never be close to the specialized databases (like Neo4j, Pinecone, Clickhouse, etc).And i've asked myself, what if, there is a database that have the same idea, but built differently? Instead of just treating it as KV database, we build specialized engines for the data.Besides that, I want it to be able to support my IOT/edge project, where i need offline sync capabilities (Currentyl still in progress).Will it work?I put it into test. I've been experimenting and researching for a year, creating multiple versions, and then I created NodeDB.Disclaimer: It is still in public beta (as of May 2026), but it really excites me if I can make this db work. And I use AI as assistant for coding and planning. It is nearly impossible to do as a solo developer without any AI assistance.Would love feedback from HN:- Are there specific features or improvements that would make it more useful?If you're interested in experimenting or contributing, the repo is here: GitHub Repo: https://github.com/nodedb-lab/nodedbLooking forward to your thoughts!
Enrichment
- Theme
- database infrastructure and developer tools
- Vertical
- Horizontal
- Function
- Data infrastructure
- Audience
- B2B
- AI stance
- Not AI
- Project type
- Commercial product
- Normalized one-liner
- multi-model database
- Manually corrected
- False
Could you build this?
No Developing a high-performance, purpose-built multi-model database with native graph and vector capabilities requires deep systems programming, storage engine design, and query optimization expertise.
What it would actually take: Building a custom database engine requires Rust, C++, or Go, implementing custom storage abstractions (e.g., LSM-trees, B+ trees), memory-mapped files, write-ahead logging (WAL), concurrent transaction management, and indexing algorithms (like HNSW for vectors and adjacency lists/indices for graphs). A vibe coder can wrap existing engines like SQLite or RocksDB, but building an original, reliable, crash-resilient multi-model engine requires specialized systems engineering and database internals knowledge.
Discussion
1 comment analyzed.
Competitors mentioned: PostgreSQL
Feature requests: Change log/event stream for reactive systems, Durable streams or hooks for update streaming, PostgreSQL logical replication compatibility
Competitors
Other products that read as similar to this one — 93 launches clear the similarity bar, closest 8 shown.
Attention rank: #84 of 94 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 194 days after the earliest competitor.
- LatticeDB · hn · 2026-08-25 · 190 upvotes · similarity 0.47
- GEDB · hn · 2026-02-16 · 9 upvotes · similarity 0.47
- TuringDB · hn · 2026-01-28 · 7 upvotes · similarity 0.46
- HelixDB · hn · 2026-06-10 · 159 upvotes · similarity 0.46
- VectorDBZ, a desktop GUI for vector databases · hn · 2026-01-01 · 13 upvotes · similarity 0.45
- UnisonDB · hn · 2025-11-01 · 17 upvotes · similarity 0.45
- BlitzGraph · hn · 2026-06-16 · 15 upvotes · similarity 0.43
- VisuaLeaf · hn · 2026-04-29 · 9 upvotes · similarity 0.43
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a data infrastructure tool for Media & entertainment yet.