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.
Implementing Knowledge Graphs in Enterprises - Some Tips and Trends | LinkedIn
Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for all applications of artificial intelligence. The development of competences and experts in th
Importing, Exploring, and Exporting Your Data with Stardog Studio
like experience for quickly importing CSV data into Stardog. To get started, just choose a database under Studio’s”Databases”tab and click on”ImportCSV.” Studio’s wizard will extract the headers (if any) from the CSV file you supply and will let you choose both a name for the class of data that the CSV represents(i.e.,the type of thing to which each row of the CSV corresponds) and the column that should be used for generating unique identifiers for instances of that class. To help you choose a truly unique identifier, the wizard will also show you just how distinct the data in each column of the CSV is, and will indicate whether or not the column you’ve chosen is likely to be a good one with respect to data integrity. Data Exploration
Improving long-form question answering by compressing search results
"We propose constructing one #knowledgegraph per query & show this method compresses information and reduces redundancy" > Improving long-form question answering by compressing search results / Angela Fan @facebookai h/t @aaranged https://ai.facebook.com/blog/research-in-brief-training-ai-to-answer-questions-using-compressed-search-results/
Learn about how AstraZeneca visualized patient journeys, answered important questions about prescriptions and diagnoses, and improved patient outcomes.
Industry-scale Knowledge Graphs: Lessons and Challenges - ACM Queue
This article looks at the knowledge graphs of five diverse tech companies, comparing the similarities and differences in their respective experiences of building and using the graphs, and discussing the challenges that all knowledge-driven enterprises face today. The collection of knowledge graphs discussed here covers the breadth of applications, from search, to product descriptions, to social networks.