- Home
- NoSQL Databases
- Graph Databases
Category: Graph Databases
This Week in Neo4j: Ops Manager Release, New .NET Courses, Cybersecurity, Twitter, Med Research, and More

Feed: Neo4j Graph Data Platform. Author: Yolande Poirier. Whether you’re running a single instance of Neo4j, or multiple databases across clusters, you will be pleased to hear about the release of the Neo4j Ops Manager. This new product makes it effortless to monitor and administer all your Neo4j databases, instances, and clusters from a central UI-based application.
Using Neo4j Ops Manager, you can instantly view the status of all databases under management. This will tell you whether all is well or if any cluster or instance needs attention. You can inspect the health of each instance, reviewing database-specific, OS, ... Read More
Neo4j Ops Manager: One Place to Centrally and Easily Manage Neo4j Databases

Feed: Neo4j Graph Data Platform. Author: Angela Zimmerman. It’s tough being part of an operations team responsible for managing databases nowadays. In the past, it was enough to have a database administrator who was proficient in SQL and knew how to operate a relational database on a single machine. But now, it seems like anybody managing databases has to be a polyglot familiar with different types of NoSQL databases. Out of all NoSQL database types, graph is the most unique compared to the aggregate NoSQL ones like document, key-value, or wide-column. Graph database adoption is growing at more than 20 ... Read More
Developers.Zed: The LinkedIn for Developers in Zambia

Feed: Neo4j Graph Data Platform. Author: Angela Zimmerman. Disruption in technology is driving change across every major industry today, and that change represents a unique opportunity for organizations of any size and value to differentiate through innovation. Whether it’s getting to Mars earlier than expected, or connecting disparate sources of information to take down a massive money laundering network, graphs are powering innovation on a global and cosmic scale. Tara Shankar Jana of Neo4j had the pleasure of speaking with Kacha Mukabe, who is a grand winner of the 2021 Leonhard Euler Idea Contest for his innovative project using Neo4j ... Read More
This Week in Neo4j: Bloom 2.3, Graph Data Science, Java, AWS, Python, Ontology, Microservices, and More

Feed: Neo4j Graph Data Platform. Author: Yolande Poirier. Graph Data Science features are now available in Bloom 2.3! Just select the Graph Data Science icon and choose from the available algorithms. The GDS plugin needs to be installed on the database for self-managed users, or you can use AuraDS.
To get an idea of what Bloom and Graph Data Science are capable of, read Zach Blumenfeld ’s blog on using graph technology on a freight forwarding logistics network. In this first blog in the series, he gets us started with experimentation and visualization of supply chain data using ... Read More
Summer social: Sake in the sun
Feed: Cambridge Intelligence. Author: Rosy Hunt. After two years of virtual company socials we rediscovered the great outdoors together last week, at our belated 10-year anniversary celebration. The party began at Dojima Brewery in Ely, where we toasted ten years of graph visualization adventures with Dojima sake in the beautiful walled Japanese gardens at Fordham Abbey. Having sampled the sake, we learned about its history and culture. A brewery tour and Matcha tea ceremony were followed by a feast of Japanese tapas and Wagyu beef, washed down with Japanese beer and natural wine. After a quick game of croquet in ... Read More
Announcing Neo4j Bloom 2.3: Supercharged With Graph Data Science

Feed: Neo4j Graph Data Platform. Author: Angela Zimmerman. All great things come in pairs:
Peanut butter and jelly (or jam, for our international readers)
Fish and chips
Gin and tonic
Simon and Garfunkel
And the list goes on… Well, for some time now, Neo4j Bloom has been a great companion to Neo4j Graph Data Science. For example, by enriching nodes with the Graph Data Science library outputs like centrality measures or community algorithms, users can apply rule-based styling in Bloom to easily visualize results. And that’s just the tip of the iceberg.With today’s latest release of Neo4j Bloom 2.3, we ... Read More
Pride at Neo4j: Thirty Years of Hope

Feed: Neo4j Graph Data Platform. Author: Angela Zimmerman. I was 11 years old when Harvey Milk gave his famous “Hope” speech on the steps of San Francisco City Hall on Gay Pride Day 1978. I became aware of Milk five months later when he was assassinated – along with San Francisco mayor George Moscone – by Dan White. That was probably the first time I’d ever heard about a homosexual in anything other than a negative light. A little more than a decade after Milk’s death, I had moved to San Francisco and come out. This was in 1990, during ... Read More
Decentralizing the internet with Syntropy & ReGraph
Feed: Cambridge Intelligence. Author: Rosy Hunt. In this blog you’ll see how Syntropy, a global team of web3 pioneers, use our network visualization toolkits to create a live journey planner for the internet, helping enterprises choose the fastest and safest routes for their data. Rising above a flaky internet Chaos reigns on the internet. It’s just something we’ve learned to live with – flaky connections, unpredictable latency, lost data. It’s frustrating and risky for personal users, and there’s even more at stake for enterprises, most of whom rely on their own internal networks as well as the public internet. For ... Read More
This Week in Neo4j: AuraDS on Vertex AI, Going Meta Series, Cypher Cheatsheet, GraphConnect Recordings, Centrality Algorithms, and More

Feed: Neo4j Graph Data Platform. Author: Yolande Poirier. Back in January, we previewed Neo4j AuraDS and Google Cloud Vertex AI’s partnership and demonstrated how you can build and deploy graph-based machine learning models. AuraDS is graph data science as a service now running as a managed service on top of GCP. With the Neo4j Graph Data Science platform, you can easily use graph structure to compute algorithms or create embeddings and increase the accuracy and reliability of machine learning pipelines. The worked example from the blog stores data in AuraDS, and computes graph embeddings with FastRP to feed into the ... Read More
The New Normal: What I Learned (or Un-Learned) at GraphConnect 2022

Feed: Neo4j Graph Data Platform. Author: Enzo. A tremendous amount of database science is devoted to the fine art of “normalization” – making your data easier for their databases to digest. Time to ask yourself: Who does normalization actually serve? Graph computing solves problems. It solves them by modeling those problems using symbols folks can readily understand, and then mapping graphs to data in a sensible, straightforward manner. It’s not always easy to throw a party around the ideal of “sensible” and “straightforward” – or if we want to go even deeper, “normal.” If anyone’s ready to throw a party ... Read More
Recent Comments