PostgreSQL as Graph database with AGE - simple example | LinkedIn
Here is a very simple example of graph with AGE PostgreSQL extension. In this example, we will assume we are trying to match a donor who can potentially donate to a patient based on the matching blood group.
Discover some of the best technical talks and videos from the NODES 2025 online conference organized by Neo4j and curated by Christian Miles from G.V().
A framework for transforming tabular (CSV, SQL) and hierarchical data (JSON, XML) into property graphs and ingesting them into graph databases (ArangoDB, Neo4j, TigerGraph). Features automatic PostgreSQL schema inference.
Check out these lance-graph benchmarks on an artificial social network dataset 👇🏽. The query suite used tests for a Cypher query workload across different dimensions. Q8/9 in this suite are especially challenging for most systems. Systems like Kùzu Inc and LadybugDB (fork of Kuzu) perform especially well because they innovate on factorization and hybrid join algorithms (WCOJ + binary joins).
The #Lance format (upon which lance-graph is built) is designed for fast random access + scans, and this benchmark is just the beginning! Stay tuned for more benchmarks and written content on this. 🚀
Many thanks to our collaborators Chunxu Tang and Beinan Wang for their hard work on this project!
lance-graph repo: https://lnkd.in/gm7iGPit
benchmark repo: https://lnkd.in/gxETZE7R
Semantic Data Modeling, Graph Query, and SQL, Together at Last?
We're connecting some parallel threads on semantic modeling and graph query with our continued focus on making SQL easier to use.
Semantic modeling is about bringing higher-level business logic definitions into the database (rather than a layer above), so they can be queried directly with SQL. We use measure columns to solve double-counted aggregates. And we model the graph relationships (joins) in the schema, making it easy to express joins with just path traversals.
#GraphLandscape2026
We’re starting the year with a fresh view of the graph landscape!
After sharing our first version of the Graph Landscape 2026 back in November, we received great feedback from the community.
Based on your input, we’ve decided to make additions, refinements, and adjustments — and created a brand new edition in PDF.
This report reflects:
👉 emerging trends across the graph ecosystem
👉 evolving technologies and use cases
👉 new and maturing players shaping the market
Happy reading!
#Technology
#GraphAnalytics
#KnowledgeGraphs
AIM MarketView: Graph Databases 2026 is now live 🔴
Graph databases are rapidly emerging as core platforms for relationship-centric analytics, knowledge graphs, and agentic AI–enabled decision systems. The AIM MarketView: Graph Databases 2026 provides a comprehensive view of the global graph database ecosystem, profiling 30 leading vendors and analyzing how platforms are evolving across scale, intelligence, and enterprise adoption.
🔍 What’s inside the report:
- Landscape of 30 graph database vendors spanning property graph, RDF/semantic, multimodel, cloud-native, and open-source architectures
- Vendor-specific use cases and commercial models for every profiled graph DB/platform.
- Deep dive into Graph + AI convergence, including GraphRAG, vector–graph integration, and graph-based reasoning
- Adoption insights across financial services, cybersecurity, life sciences, telecom, retail, manufacturing, and the public sector
As enterprises move beyond isolated analytics toward context-aware, connected intelligence, graph databases are becoming foundational to both AI-native architectures and agentic systems.
Aerospike | Altair | Amazon | Arango | BangDB | FalkorDB | Fluree | Franz Inc. | Google | Graphwise | HugeGraph | Hypermode | InfiniteGraph | JanusGraph | Microsoft Azure | Memgraph | Neo4j | NebulaGraph, powered by Vesoft | OrientDB | Oracle | Oxford Semantic Technologies (RDFox) | Progress MarkLogic - Progress Data Platform | Rocketgraph | Sparsity Technologies (Sparksee) | Stardog | TerminusDB | TigerGraph | Ultipa #VelocityGraph
#GraphDatabases #KnowledgeGraphs #DataEngineering #AgenticAI #GraphRAG #AIMMarketView #AIM
Learn graph database fundamentals, query languages, and implementation patterns for AI systems. Covers GraphRAG, knowledge graphs, and performance optimization.
An OWL ontology and RDF knowledge graph of the top 100 IMDb movies, modeled in Protégé and stored in GraphDB. Demonstrates semantic modeling, data ingestion, and SPARQL querying.
An OWL ontology and RDF knowledge graph of the top 100 IMDb movies, modeled in Protégé and stored in GraphDB. Demonstrates semantic modeling, data ingestion, and SPARQL querying. - marcusv02/film-k...
In this episode of Founders Discussion, TuringDB founders Adam Amara and Rémy Boutonnet sit down to discuss one of the most important and often overlooked ca...
Why Versioning Matters for Graph Databases | Founders Discussion with Adam & RémyTap to unmute2xWhy Versioning Matters for Graph Databases | Founders Discussion with Adam & RémyTuringDB 47 views 13 days agoSearchCopy linkInfoShoppingIf playback doesn't begin shortly, try restarting your device.Pull up for precise seeking7:44•Up nextLiveUpcomingCancelPlay nowTuringDBSubscribeSubscribedTuringDB - A new fast graph database engine - The Engineering Discussion @CTO Remy Boutonnet29:38You're signed outVideos that you watch may be added to the TV's watch history and influence TV recommendations. To avoid this, cancel and sign in to YouTube on your computer.CancelConfirmHideShareInclude playlistAn error occurred while retrieving sharing information. Please try again later.0:010:21 / 37:21Live•Watch full video••4:33First Dates: Βρήκαμε το χειρότερο ραντεβού όλων των εποχών | Luben TVLuben TV2.4m views • 2 years agoLivePlaylist ()Mix (50+)8:29How Jacob Collier Convinced The World He's A GeniusJacob de Jongh343k views • 2 months agoLivePlaylist ()Mix (50+)1:26:33Tom & Tapp: From Navy Flight Decks to Solving the Healthcare Data PuzzleLast Visit First 1 view • 36 minutes agoLivePlaylist ()Mix (50+)9:26Φραπες best ofrednight12345651k views • 8 days agoLivePlaylist ()Mix (50+)13:35We Tried Trunk-Based Development... The Results Were Shocking.Modern Software Engineering30k views • 11 days agoLivePlaylist ()Mix (50+)19:40The Exact Moment The AI Bubble Burst…Fads216k views • 1 day agoLivePlaylist ()Mix (50+)3:32Chernobyl Accident - Simulation only (no talk)Higgsino physics6.6m views • 1 year agoLivePlaylist ()Mix (50+)17:54Top 20 Hilariously Out of Touch Celebrity MomentsWatchMojo.com1.3m views • 6 months agoLivePlaylist ()Mix (50+)12:51Peter Can't Believe A Pyramid Scheme Business Model's Being Pitched | Dragons' DenDragons' Den9.8m views • 6 years agoLivePlaylist ()Mix (50+)8:58Honest Trailers | Stranger Things S5 (Part 1)Screen Junkies519k views • 12 days agoLivePlaylist ()Mix (50+)4:37Δημοσιογράφος ανταλλάσσει ΕΠΙΚΕΣ ΠΡΟΣΒΟΛΕΣ με τον Βαρουφάκη σε μία "ΧΑΡΟΥΜΕΝΗ" συνέντευξηWatchdog TV274k views • 7 months agoLivePlaylist ()Mix (50+)18:51🚀ASTRAIOS Podcast Series: Success Stories in EO & GNSS | François CaronASTRAIOS Project10 views • 10 days agoLivePlaylist ()Mix (50+)
Why Versioning Matters for Graph Databases
Discover what’s new this week in graph technology, including a big acquisition, a pre-seed investment, a 360-degree take on Connected Data London, and more.
G.V() Snatches Up £500,000 in First Cheque Investment from Techstart Ventures
Learn all about G.V()’s recent $658,000 pre-seed investment round from Techstart Ventures and what’s ahead for the product, company, and graph community.