Why an Open Source JSON-LD Database
We are pleased to launch a public preview of an open source JSON-LD database which combines the simplicity of a document db with the analytical power of semantic graph. We hope it is approachable for most any developer while having the capabilities, when needed, for data interoperability, embedded cell-level security (ReBAC style), rich shape/schema restrictions, data provenance (time travel), and fact inferencing. Why did our team at Fluree build this? Data is increasingly critical for great decision making, AI, and more. The way we typically store and manage data, mainly as an…
Why an Open Source JSON-LD Database launched on November 30, 2023 with 16 votes, #1,319 of 4,333 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This is an open source JSON-LD database that combines document database simplicity with semantic graph capabilities. Built by Fluree, it serves developers who need to manage and analyze data effectively. Key features include cell-level security, schema restrictions, data provenance with time-travel capabilities, and fact inferencing, making it suitable for applications requiring data interoperability and complex access control alongside traditional database operations.
written from the facts on this page · September 2026
From the sources
FlureeDB is the verifiable knowledge graph database — temporal RDF with complete history, integrated search, triple-level access control, and git-like branching in one Rust binary.
Live webinar Oct 1 — save your seat Live webinar Oct 1 — Turning Unstructured Data Into Knowledge Your AI Can Trust. Save your seat Temporal, verifiable, standards-compliant. RDF triples with complete history, integrated search, and fine-grained access control — in a singlefrom flur.ee
In the maker’s words, at launch
We are pleased to launch a public preview of an open source JSON-LD database which combines the simplicity of a document db with the analytical power of semantic graph. We hope it is approachable for most any developer while having the capabilities, when needed, for data interoperability, embedded cell-level security…
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HelixDB – A graph database built on object storageJun 2026 · github.com · ▲159Hey 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…
HelixDB – Open-source vector-graph database for AI applications (Rust)2025 · github.com · ▲237Hey 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.…
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A proof-of-concept FoundationDB based network block device backend2018 · github.com · ▲192A totally proof-of-concept FoundationDB based network block device backend - dividuum/fdb-nbd
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