the rise of graph databases relationships--this is the relationship between paul and jelme note that the relationship has directionit' paul who "knowsjelme and not the other way around user and user both represent people and could therefore be grouped labels--in graph databaseone can group nodes by using labels user and user could in this case both be labeled as "userconnected data often contains many more entities and connections in figure we can see more extensive graph two more entities are includedcountry with the name cambodia and country with the name sweden two more relationships exist"has_been_inand "is_born_inin the previous graphonly the entities included propertynow the relationships also contain property such graphs are known as property graphs the relationship connecting the nodes user and country is of the type "has_been_inand has as property "datewhich represents data value similarlyuser is connected to country but through different type of relationshipwhich is of the type "is_born_innote that the types of relationships provide us context of the relationships between nodes nodes can have multiple relationships knows user user namepaul last namebeun namejelme last nameragnar has_been_in is_born_in datedobcountry country namecambodia namesweden relationship of type "is_born_inwith property figure more complicated connected data example where two more entities have been included (country and country and two new relationships ("has_been_inand "is_born_in"this kind of representation of our data gives us an intuitive way to store connected data to explore our data we need to traverse through the graph following predefined paths to find the patterns we're searching for what if one would like to know where paul has beentranslated into graph database terminologywe' like to find the pattern "paul has been in to answer thiswe' start at the node with the