Discover the major differences and trade-offs between imperative and declarative query languages as we define and discuss the strengths and weaknesses of each.

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

New MarkLogic Data Hub Service delivers both agile data integration and agile data infrastructure—with unmatched security and governance, and predictable costs.

Discover Neo4j Bloom, the latest product from the Neo4j team. This graph data visualization tool helps traditional Neo4j users communicate with their non-technical peers in a simple manner that reveals and explains the concepts of data connectedness for all people, regardless of technical background.

The 1990s and 2000s saw the rise of the relational databases for transaction processing (OLTP) as well as analytical processing (OLAP). As the volume and

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...

JanusGraph 0.3.0 is released! Congrats to the 27 contributors who made the release possible. https://t.co/za3cH9pG6a @JanusGraph @linuxfoundation #TinkerPop #graphdb pic.twitter.com/5SxDMNXRsg— Jason Plurad (@pluradj) August 7, 2018

Discover how knowledge graphs are the key to delivering relevant search results, and how they are used for a wide range of use cases and industries.

Bye Bye Silos! Those who stay on their islands will fall back. This statement is valid on nearly any level of our increasingly complex society, ranging from whole cultural areas down to single individuals.

AI is in its infancy and cannot be left unattended. Whether unintentional or by malicious design, algorithms behaving unexpectedly are now a fact of life.

Learn how to manage Azure Cosmos DB resources by using the Azure portal, PowerShell, CLI, and Azure Resource Manager templates

I usually mention both as unique/key features of RDF: global identifiers and zero-cost merge— Martynas Jusevicius (@namedgraph) June 8, 2018

Graph Examples on your Desktop

For the milestone of the 3.4 release, we’ve implemented a set of information retrieval features exposed via new database object View.

“Which #RDF graph partitioning technique gives better performance in cluster triplestore? checkout our empirical evaluation of RDF graph partitioning techniques in different architectures. https://t.co/wRlrR8lOSa #EKAW2018 #BigData”

We’re pleased to announce a major new release of Stardog that includes native support for unifying MongoDB data silos in Stardog.

With the emergence of offerings on both AWS (Neptune) and Azure (CosmosDB) within the past year it is fair to say that graph databases are of the hottest trend…

Just recently A* Algorithm was added to Neo4j graph algorithms and I decided to show how nicely APOC spatial functions fit with it as it uses GPS location for heuristic. Import I found this cool gi…

Among the Neo4j 3.4 database enhancements are horizontal scaling, 3D geospatial search, performance improvements of more than 50 percent and numerous operational improvements.

SAN FRANCISCO, May 2, 2018 -- Neo4j, the leading platform for connected data, today announced Neo4j 3.4, which includes horizontal scaling, performance

In this week's #twin4j @amyhodler interviews Alastair Green, @boggle, and @aethelraed about the GQL proposal that was published last week.https://t.co/HWlcwFIEwE#neo4j pic.twitter.com/xYwPXZcC55— Neo4j (@neo4j) May 27, 2018

Neo4j tunes its graph engine for AI applications - SiliconANGLE

New software-as-a-service application automatically adds and removes query processing capacity to a database cluster as workload demand rises and falls, resulting in agility and responsiveness for end...

NodeXL Graph Gallery, a collection of network graphs created by NodeXL.

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Discover how Pypher allows you to tap into the power of the Cypher query language in order to use pure Python when querying connected data, making your Cypher code easier to wrangle and manage in the long run for either the Neo4j graph database or in any other Cypher-enabled graph technology.

Titan, Tinkerpop, Neo4j, ArrangoDB, OrientDB, but I still have a fondness for grep/sed/awk and flatfiles.