#graphdb — Public Fediverse posts

Deploy a production-ready ArcadeDB cluster on Kubernetes in one command with the official Helm chart. From zero to a single pod in 30 seconds. arcadedb.com/blog/deploy-... #k8s #graphdb #multimodel

Let me use this time to write down what I'm building. Not what's in my git repos. What's in my head.

The system is distributed. And distribution is optional. Each node has their own state, their own runtime, their own persistence. All one thing.

Each node in the system is a content-addressed Merkle Tree. Not SHA. Coincidence. A spectral coincidence hash. 5 dimensions. (1 more than spacetime.)

A spectral coincidence hash describes the structure of the data. You can do math on that. Spectral graph analysis. The world becomes navigatable. Because everything has an address.

Each computation. Each inference. Each failure. Each partial success. Each time information was lost. All of it enters the graph. All of it local. All of it distributed if needed. (For the BEAM engineers: it's an mnesia backend.)

A system that doesn't only know what it knows and what it doesn't. A system that knows how it got there. And AI that lives inside that knowledge.

That's what I'm building.

#SovereignTechFellowship grant application open. Release on the horizon. Wish me luck!

#OpenSource #EUTech #AI #Erlang #Fortan #Rust #GraphDB

Let me use this time to write down what I'm building. Not what's in my git repos. What's in my head.

The system is distributed. And distribution is optional. Each node has their own state, their own runtime, their own persistence. All one thing.

Each node in the system is a content-addressed Merkle Tree. Not SHA. Coincidence. A spectral coincidence hash. 5 dimensions. (1 more than spacetime.)

A spectral coincidence hash describes the structure of the data. You can do math on that. Spectral graph analysis. The world becomes navigatable. Because everything has an address.

Each computation. Each inference. Each failure. Each partial success. Each time information was lost. All of it enters the graph. All of it local. All of it distributed if needed. (For the BEAM engineers: it's an mnesia backend.)

A system that doesn't only know what it knows and what it doesn't. A system that knows how it got there. And AI that lives inside that knowledge.

That's what I'm building.

#SovereignTechFellowship grant application open. Release on the horizon. Wish me luck!

#OpenSource #EUTech #AI #Erlang #Fortan #Rust #GraphDB

I just published a blog post that tells of my early experience with Gastown, a multi-agent workspace manager, in trying to build pure javascript Gremlator implementation: https://stephen.genoprime.com/snippet/2026/04/03/snippet-23.html #graphdb

Knowledge graphs are useful representations for knowledge bases, #pkm, #AImemory systems, #GraphRAG, intelligent tutoring systems, etc., and usually implemented in graph databases. LadybugDB, a fork of the discontinued Kuzu, is a lightweight embedded (like SQLite) graph database: https://github.com/LadybugDB/ladybug
Sample applications in development: https://github.com/inventivepotter/dotmd & https://github.com/tejzpr/Smriti-MCP
See also Grafeo: https://github.com/GrafeoDB/grafeo
#AIEd #AIEngineering #KnowledgeGraph #GraphDB #graphdatabase

Knowledge graphs are useful representations for knowledge bases, #pkm, #AImemory systems, #GraphRAG, intelligent tutoring systems, etc., and usually implemented in graph databases. LadybugDB, a fork of the discontinued Kuzu, is a lightweight embedded (like SQLite) graph database: https://github.com/LadybugDB/ladybug
Sample applications in development: https://github.com/inventivepotter/dotmd & https://github.com/tejzpr/Smriti-MCP
See also Grafeo: https://github.com/GrafeoDB/grafeo
#AIEd #AIEngineering #KnowledgeGraph #GraphDB #graphdatabase

Also if you are into #rdf and #knowledgegraph you have heard of tinker pop gremlin 👹 then the following pipeline might remind you some good souvenir:

´´´
(let ((g (make-graph gremlin-n gremlin-e 10 12345)))
(display "Graph: ")
(display gremlin-n)
(display " vertices, ")
(display gremlin-e)
(display " edges/vertex, 10 groups")
(newline)
(let ((tri (time
(traverse g
(V)
(as a)
(out)
(as b)
(where (same-group? g a b))
(out)
(as c)
(where (same-group? g a c))
(where (edge? g c a))
(count)))))
(display tri)
(display " triangles")
(newline)))
´´´

ref: https://github.com/amirouche/seed/blob/seed3/src/src/seed3/benchmarks/gremlin-pipeline.seed3

#scheme #graphdb

Also if you are into #rdf and #knowledgegraph you have heard of tinker pop gremlin 👹 then the following pipeline might remind you some good souvenir:

´´´
(let ((g (make-graph gremlin-n gremlin-e 10 12345)))
(display "Graph: ")
(display gremlin-n)
(display " vertices, ")
(display gremlin-e)
(display " edges/vertex, 10 groups")
(newline)
(let ((tri (time
(traverse g
(V)
(as a)
(out)
(as b)
(where (same-group? g a b))
(out)
(as c)
(where (same-group? g a c))
(where (edge? g c a))
(count)))))
(display tri)
(display " triangles")
(newline)))
´´´

ref: https://github.com/amirouche/seed/blob/seed3/src/src/seed3/benchmarks/gremlin-pipeline.seed3

#scheme #graphdb

ArcadeDB v26.2.1 is full of surprises. Did you know we introduced a new SQL parser, built with ANTLR (instead of JavaCC) that is 75.9% faster? blog.arcadedb.com/new-sql-parser #multimodel #graphdb #sql

With ArcadeDB 26.2.1 you can schedule automatic backups. Check out this new feature: blog.arcadedb.com/introducing-... #graphdb #multimodel

blog.arcadedb.com/introducing-au...

ArcadeDB 26.2.1 is out! Biggest highlights: - @Neo4j Bolt protocol support - use standard Neo4j drivers - Full @openCypher TCK compliance - New SQL parser - SQL Triggers (SQL, JS, Java) - Scheduled Backups 200+ issues closed github.com/ArcadeData/a... #graphdb #multimodel

Release 26.2.1 · ArcadeData/ar...

ArcadeDB 26.2.1 is out! Biggest highlights: - @Neo4j Bolt protocol support - use standard Neo4j drivers - Full @openCypher TCK compliance - New SQL parser - SQL Triggers (SQL, JS, Java) - Scheduled Backups 200+ issues closed github.com/ArcadeData/a... #graphdb #multimodel

Release 26.2.1 · ArcadeData/ar...

ArcadeDB v26.1.1 is out! New Native OpenCypher Engine, huge LSM Vector updates (Quantization, PQ and much more), 92 total issues resolved (!) github.com/ArcadeData/a... #ArcadeDB #GraphDB #OpenCypher #VectorSearch #Database #OpenSource

Release 26.1.1 · ArcadeData/ar...

ArcadeDB v26.1.1 is out! New Native OpenCypher Engine, huge LSM Vector updates (Quantization, PQ and much more), 92 total issues resolved (!) github.com/ArcadeData/a... #ArcadeDB #GraphDB #OpenCypher #VectorSearch #Database #OpenSource

Release 26.1.1 · ArcadeData/ar...

olu 0.9.0 RELEASED

olu is a JSON document store with automatic graph relationships.

Repo:
https://github.com/ha1tch/olu

Manual
https://github.com/ha1tch/olu/blob/main/MANUAL.md

Release binaries:
https://github.com/ha1tch/olu/releases/tag/v0.9.0

Use cases:

• Rapid prototyping
• Small to medium CRUD APIs
• IoT asset/device management
• Multi-tenant SaaS backends
• Content management systems
• Configuration stores with relationships
• Graph analysis and traversal

Features

• REST API: Full CRUD, filtering, pagination, field projection, REF embedding
• OQL: (sql-like subset) — SELECT, INSERT, UPDATE, DELETE, WHERE, ORDER BY, TOP, GROUP BY, aggregates (COUNT, SUM, AVG, MIN, MAX)
• Sulpher: Cypher-like graph queries — MATCH patterns, shortest path, common neighbours, incoming/outgoing traversal, cycle detection, node degree

New in 0.9.0:

• SQLite + FTS5 full-text search
• REF field embedding with configurable depth
• Graph cycle detection (warn/error/ignore)
• JWT/API key authentication
• Rate limiting with per-key quotas
• Prometheus metrics
• Multi-tenant isolation (path or strict mode)
• Docker Compose profiles for dev/test/prod

250+ unit tests, stress tests with race detector, 17 Docker integration tests. Redis cache at 36K ops/sec.

#olu #database #json #golang #foss #datastore #graph #graphdb #REST

In room Omega 2, Taras Kloba is presenting about using PostgreSQL as a graph database

#pgconfeu #postgresql #database #riga #graphdb

rserv and olu

This paints a clearer picture of the evolution of the two projects and API coverage over the last 12 months. The goal is to bring Olu to api parity with rserv 0.5.3 targeting completion sometime between March and June 2026.

rserv 0.5.3

• https://github.com/ha1tch/rserv

olu 0.7.0

• https://github.com/ha1tch/olu

#olu #graphdb #documentdb #foss #golang

Olu

I'm considering adding this query language syntax that looks like SQL but operates on Olu's graphs.

#olu #graphdb #golang #foss