Crossing the Chasm - Eight Prerequisites For A Graph Query Language
Prelude In December, I wrote a Quora post on the pros and cons of graph databases. I shared two cons pervasive in the market today: the difficulty of finding proficient graph developers, and how non-standardization on a graph query language is slowing down enterprise adoption,...
The time is ripe for an international standard graph query language. Industry vendors including Neo4j have called this out, and we at TigerGraph wholeheartedly agree. As graphs continue to see widespread adoption, we have certainly reached a tipping point for our industry. Still, it is...
by Dr. Xu Yu, CEO and Dr. Victor Lee, Director of Product Management [Excerpted from the eBook Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics] Until recently, graph database designs fulfilled some but not all of the graph analytics...
Recently RedisGraph published a blog [1], comparing their performance to that of TigerGraph’s, following the tests [2] in TigerGraph’s benchmark report [3], which requires solid performance on 3-hop, 6-hop, and even 10-hop queries. Multi-hop queries on large data sets are the future of graph analytics....
‘You’re Stupid If You Don’t Get Scared’: When Amazon Goes From Partner to Rival
The Seattle giant’s cloud-computing business offers a look inside its model for expanding—even when it means moving in on allies’ turf. Some partners praise the unit’s chief for straddling the line between friend and competitor.
Type safety in the world of graph databases by Michael Pollmeier
This video was recorded at Scala Days Berlin 2018 Follow us on Twitter @ScalaDays or visit our website for more information http://scaladays.org More information and the abstract can be found here: https://eu.scaladays.org/lect-6908-type-safety-in-the-world-of-graph-databases.html
How to take advantage of scale out graph in Azure Cosmos DB : Build 2018
Real-world data is naturally connected. Learn how to create graph database applications on Azure Cosmos DB and explore the different solutions that it provides to common data scenarios in the enterprise. We will also cover customer cases that currently leverage graph databases in their day-to-day workloads. Create a Free Account (Azure): https://aka.ms/azft-cosmos
Distributed Data Show Episode 63: Building Applications on Graph Databases with Josh Perryman
We talk with Josh Perryman of Expero about his experiences building highly scalable and performant applications using relational databases, graph databases and sometimes even both at the same time. Highlights 0:15 - Jeff welcomes Josh to the show and finds out what a “data junkie” is, 1:31 - Josh got into graph databases by way of consulting in high performance computing - a client struggling with relational performance asked him to look at graph solutions 3:41 - He started by working on proof of concepts with multiple graph databases 4:49 - In this particular case, it turned out that it wa...
Graham Ganssle, Data Science Lead at Expero, gave this introduction to Graph Convolutional Networks at a recent meetup of Austin Data Geeks / Austin AI. More graph videos coming soon! Join The Graph Community on Linkedin: https://www.linkedin.com/groups/3965793/ For expert graph consulting and implementation, visit: http://experoinc.com Abstract Is this group of delis a money laundering ring, or are they simply exchanging provolone? Why does Devin have so many Facebook friends, and I only have a handful? The answer to one of these questions is obvious (because I’m a nerd giving an ML presen...
Traversing Scalable Graphs with Azure Cosmos DB's Gremlin API - BRK3183
Real-world data is naturally connected. In this session, we provide an overview of the Graph API in Azure Cosmos DB and explain how our enterprise customers use it today to provide new insights on their data. You can query the graphs with millisecond latency and evolve the graph structure and schema easily. We also cover customer cases that currently leverage graph databases in their day-to-day workloads.
Google ponders the shortcomings of machine learning
Scientists of AI at Google's Google Brain and DeepMind units acknowledge machine learning is falling short of human cognition and propose that using models of networks might be a way to find relations between things that allow computers to generalize more broadly about the world.
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Idevnews | ArangoDB Update Makes It Easier for App Developers To Work with Multiple Data Models
ArangoDB, an open source native multi-model database, is adding a new search feature to let developers efficiently interact with multiple data models by using just one technology and one query language. IDN speaks with ArangoDB CTO Dr. Frank Celler.