Transitive Queries & Reasoning

One of the most powerful features of graph databases is the ability to traverse relationships transitively—following chains of connections without knowing how deep they go.

The Challenge

HR needs to answer: "Who are ALL the people who report to the CTO, directly or indirectly?"

With only direct relationship queries, you'd need to:

Find Marcus Johnson's direct reports (Alex, Jordan)
Find their direct reports (Emma, Michael, Sophia, James, Olivia, William)
Continue until you run out of levels

This is tedious and requires knowing the org depth in advance. With transitive queries, it's a single query.

Transitive Path Queries

The * modifier enables transitive traversal. Let's find everyone under Marcus Johnson:

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": {
    "?person": ["schema:givenName", "schema:familyName", "org:title"]
  },
  "where": { "@id": "?person", "org:reportsTo*": {"@id": "org:people/marcus-johnson"} }
}

The reportsTo* pattern follows the reportsTo chain zero or more times. This returns:

Alex Rivera (direct report)
Jordan Patel (direct report)
Emma Wilson (reports to Alex)
Michael Brown (reports to Alex)
Sophia Martinez (reports to Alex)
James Taylor (reports to Jordan)
Olivia Garcia (reports to Jordan)
William Anderson (reports to Jordan)

info

The * modifier means "zero or more hops." Use + for "one or more hops" if you want to exclude the starting node.

Management Chain (Upward Traversal)

Find everyone in William Anderson's management chain up to the CEO:

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": {
    "?manager": ["schema:givenName", "schema:familyName", "org:title"]
  },
  "where": { "@id": "org:people/william-anderson", "org:reportsTo+": "?manager" }
}

Result (in order of the chain):

Jordan Patel (Product Lead)
Marcus Johnson (CTO)
Sarah Chen (CEO)

Count Reports at Each Level

How many people report to each manager (directly and indirectly)?

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": ["?managerName", "(count ?report)"],
  "where": [
    { "@id": "?manager", "@type": "org:Person", "schema:givenName": "?managerName" },
    { "@id": "?report", "org:reportsTo+": "?manager" }
  ],
  "groupBy": "?managerName",
  "orderBy": [{"desc": "(count ?report)"}]
}

This shows Sarah Chen with the most reports (everyone), followed by Marcus Johnson, etc.

Find Common Manager

Who is the lowest common manager of Emma Wilson and James Taylor?

This requires finding where their management chains intersect:

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": {
    "?commonManager": ["schema:givenName", "schema:familyName", "org:title"]
  },
  "where": [
    { "@id": "org:people/emma-wilson", "org:reportsTo+": "?commonManager" },
    { "@id": "org:people/james-taylor", "org:reportsTo+": "?commonManager" }
  ]
}

Result: Marcus Johnson and Sarah Chen (both are in both chains). Marcus is the lowest common manager.

Organizational Depth

How deep is the reporting structure from the CEO?

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": ["?level", "(count ?person)"],
  "where": [
    { "@id": "?person", "@type": "org:Person" },
    ["bind", "?level", "(count (path org:people/sarah-chen ^org:reportsTo* ?person))"]
  ],
  "groupBy": "?level",
  "orderBy": "?level"
}

warning

Path length queries can be more complex. The example above shows the concept—actual syntax may vary based on Fluree version.

All Engineering Staff

Find everyone in Engineering and its sub-departments (Platform, Product):

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": {
    "?person": ["schema:givenName", "schema:familyName", "org:title"],
    "?deptName": []
  },
  "where": [
    { "@id": "?person", "@type": "org:Person", "org:department": "?dept" },
    { "@id": "?dept", "org:parentDepartment*": {"@id": "org:departments/engineering"}, "schema:name": "?deptName" }
  ]
}

This finds people whose department is Engineering or has Engineering as an ancestor.

Skill Gap Analysis

Find skills that exist under the CTO but not on the Platform team:

{
  "@context": {
    "org": "https://org-example.com/ns/",
    "schema": "http://schema.org/"
  },
  "select": ["?skillName"],
  "where": [
    { "@id": "?person", "org:reportsTo*": {"@id": "org:people/marcus-johnson"} },
    { "@id": "?ps", "org:person": "?person", "org:skill": "?skill" },
    { "@id": "?skill", "schema:name": "?skillName" },
    {
      "minus": [
        { "@id": "?platformPerson", "org:department": {"@id": "org:departments/engineering/platform"} },
        { "@id": "?platformPs", "org:person": "?platformPerson", "org:skill": "?skill" }
      ]
    }
  ]
}

The minus clause excludes skills that exist on the Platform team.

Comparison: SQL vs Graph

In SQL, finding all reports under a manager requires a recursive CTE:

WITH RECURSIVE reports AS (
  SELECT id, name, title, reports_to
  FROM people
  WHERE reports_to = 'marcus-johnson'
  UNION ALL
  SELECT p.id, p.name, p.title, p.reports_to
  FROM people p
  JOIN reports r ON p.reports_to = r.id
)
SELECT * FROM reports;

In Fluree, it's simply:

{
  "select": { "?person": ["*"] },
  "where": { "@id": "?person", "org:reportsTo*": {"@id": "org:people/marcus-johnson"} }
}

Summary

Transitive query patterns:

Pattern	Meaning
`reportsTo*`	Zero or more hops (includes self)
`reportsTo+`	One or more hops (excludes self)
`parentDepartment*`	Traverse department hierarchy
Upward traversal	Find all managers in chain
Common ancestor	Find shared manager

These patterns make organizational queries natural and efficient, without the complexity of recursive SQL or manual graph traversal.

The Challenge​

Transitive Path Queries​

Management Chain (Upward Traversal)​

Count Reports at Each Level​

Find Common Manager​

Organizational Depth​

All Engineering Staff​

Skill Gap Analysis​

Comparison: SQL vs Graph​

Summary​