OrientDBNew patch release out with minor fixes in backup scheduling and view refresh, release notes https://github.com/orientechnologies/orientdb/releases/tag/3.2.50
ArcadeDBArcadeDB 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...
Release 26.2.1 · ArcadeData/ar...
Jan KoesterA deep ontology is a virtue, but recursion scales poorly.
In the humanities, we crave nuance. In the engine room, we crave performance.
By trading recursive graph traversals for materialized paths, we achieve both without sacrifice.
https://resonism.substack.com/p/breaking-the-curse-of-recursion
New patch release with fixes in memory usage and dependency updates https://github.com/orientechnologies/orientdb/releases/tag/3.2.49
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...
Release 26.1.1 · ArcadeData/ar...
2025 year-recap post for #orientdb https://orientdb.dev/news/orientdb-development-stats-2025/ enjoy the read
Uncertainty is not noise.
If we force genuinely ambiguous data into binary choices to fill our Knowledge Graphs, we risk an AI that has no choice but to claim facts where a human expert would express doubt.
Full read on Substack: https://resonism.substack.com/p/uncertainty-is-invaluable
sayzardAvi Chawla (@_avichawla)
FalkorDB의 GitHub 저장소 링크를 공유하는 트윗입니다. 앞서 소개된 고성능 오픈소스 그래프 DB 프로젝트의 공식 코드 리포지토리로, 개발자에게 스타(star)를 권장하고 있습니다.
Avi Chawla (@_avichawla)
새로운 오픈소스 그래프 DB가 Neo4j보다 496배 빠르다고 주장하는 내용입니다. 전통적 그래프 DB는 노드와 엣지를 저장하고 조회 시 '포인터 체이싱' 방식으로 탐색하는데, 이 게시물은 성능 차이와 그 원리를 설명하려고 합니다.
Avi Chawla (@_avichawla) on X
This new graph DB is 496x faster than Neo4j! (open-source) Let me break down why: A traditional graph DB stores two things: nodes (entities) and edges (relationships between them). When you query a traditional graph DB, it traverses by "pointer chasing": → Start at a node
New update of what happen in #OrientDB last 3 months is here https://orientdb.dev/news/orientdb-work-in-progress-update-2025-q4/ have a good read