Properties¶

Properties are key-value pairs stored on nodes and edges. Grafeo supports a rich set of property types.

Supported Types¶

Type	Example	Description
`Boolean`	`true`, `false`	True/false values
`Int64`	`42`, `-100`	64-bit signed integers
`Float64`	`3.14`, `-0.5`	64-bit floating point
`String`	`'hello'`	UTF-8 text
`Vector`	`[0.1, 0.2, 0.3]`	f32 array for embeddings
`List`	`[1, 2, 3]`	Ordered collection
`Map`	`{key: 'value'}`	Key-value collection
`Date`	`'2024-01-15'`	Calendar date (ISO 8601)
`Time`	`'14:30:00'`	Time of day with optional timezone
`Duration`	`'P1Y2M3D'`	ISO 8601 duration (months, days, nanoseconds)
`DateTime`	`'2024-01-15T10:30:00Z'`	Date and time (microsecond precision)
`Null`	`null`	Absence of value

Using Properties¶

Setting Properties¶

INSERT (:Product {
    name: 'Widget',
    price: 29.99,
    in_stock: true,
    tags: ['electronics', 'sale'],
    metadata: {category: 'gadgets', sku: 'WDG-001'}
})

Querying Properties¶

-- Simple property access
MATCH (p:Product)
RETURN p.name, p.price

-- Property comparisons
MATCH (p:Product)
WHERE p.price < 50 AND p.in_stock = true
RETURN p.name

-- List operations
MATCH (p:Product)
WHERE 'sale' IN p.tags
RETURN p.name

Updating Properties¶

-- Set a property
MATCH (p:Product {name: 'Widget'})
SET p.price = 24.99

-- Set multiple properties
MATCH (p:Product {name: 'Widget'})
SET p.price = 24.99, p.on_sale = true

-- Remove a property
MATCH (p:Product {name: 'Widget'})
REMOVE p.on_sale

Null Handling¶

-- Check for null
MATCH (p:Person)
WHERE p.email IS NULL
RETURN p.name

-- Check for not null
MATCH (p:Person)
WHERE p.email IS NOT NULL
RETURN p.name, p.email

-- Coalesce null values
MATCH (p:Person)
RETURN p.name, coalesce(p.email, 'no email') AS email

Temporal Properties¶

Grafeo supports temporal types for dates, times and durations with ISO 8601 formatting.

Creating Temporal Properties¶

GQL typed literal syntax:

MATCH (p:Person {name: 'Alix'})
SET p.birthday = DATE '1990-06-15'

MATCH (e:Event {name: 'Meeting'})
SET e.start_time = TIME '14:30:00'

MATCH (t:Task {name: 'Sprint'})
SET t.length = DURATION 'P2W3D'

Cypher function syntax:

MATCH (p:Person {name: 'Alix'})
SET p.birthday = date('1990-06-15')

MATCH (e:Event {name: 'Meeting'})
SET e.length = duration('PT2H30M')

Temporal Comparisons¶

-- GQL
MATCH (p:Person)
WHERE p.birthday > DATE '2000-01-01'
RETURN p.name

-- Cypher
MATCH (p:Person)
WHERE p.birthday > date('2000-01-01')
RETURN p.name

Temporal Arithmetic¶

-- Date + Duration = Date
RETURN DATE '2024-01-15' + DURATION 'P1M' AS next_month
-- 2024-02-15

-- Date - Date = Duration
RETURN DATE '2024-03-15' - DATE '2024-01-01' AS diff
-- P74D

-- Duration + Duration = Duration
RETURN duration('P1Y') + duration('P6M') AS combined
-- P1Y6M

Component Extraction¶

-- Cypher extraction functions
RETURN year(date('2024-03-15')) AS y,
       month(date('2024-03-15')) AS m,
       day(date('2024-03-15')) AS d

RETURN hour(time('14:30:45')) AS h,
       minute(time('14:30:45')) AS m,
       second(time('14:30:45')) AS s

Duration Format¶

Durations use ISO 8601 format: OnYnMnDTnHnMnS

Component	Meaning	Example
`P`	Period marker (required)	`P1Y`
`nY`	Years	`P2Y` = 2 years
`nM`	Months (before T)	`P3M` = 3 months
`nD`	Days	`P10D` = 10 days
`T`	Time separator	`PT5H` = 5 hours
`nH`	Hours	`PT12H` = 12 hours
`nM`	Minutes (after T)	`PT30M` = 30 minutes
`nS`	Seconds	`PT45S` = 45 seconds

Combined example: P1Y2M3DT4H5M6S = 1 year, 2 months, 3 days, 4 hours, 5 minutes, 6 seconds.

Vector Properties¶

Vectors store dense embeddings for similarity search. See the Vector Search Guide for comprehensive documentation.

Storing Vectors¶

-- Store embeddings on nodes
INSERT (:Document {
    title: 'Introduction to Graphs',
    embedding: [0.1, 0.2, 0.3, -0.1, 0.5]
})

-- Store with specific dimensions (384-dimensional embedding)
INSERT (:Product {
    name: 'Widget',
    description_embedding: $embedding  -- Passed as parameter
})

Querying Vectors¶

-- Find similar documents using cosine similarity
MATCH (d:Document)
WHERE cosine_similarity(d.embedding, $query_embedding) > 0.8
RETURN d.title

-- Find k-nearest neighbors
MATCH (d:Document)
RETURN d.title, cosine_distance(d.embedding, $query) AS distance
ORDER BY distance
LIMIT 10

Distance Functions¶

Function	Description
`cosine_similarity(a, b)`	Cosine similarity (1 = identical, 0 = orthogonal)
`cosine_distance(a, b)`	1 - cosine_similarity
`euclidean_distance(a, b)`	L2 distance
`dot_product(a, b)`	Inner product
`manhattan_distance(a, b)`	L1 distance