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Canadian property datasets

Six datasets. One pipeline. All ten provinces. Weekly refresh since 2014. Everything BrightCat ships, in one view.

BrightCat operates six property datasets from a single underlying pipeline. Each dataset is available through all three delivery paths (Snowflake Marketplace, MCP Connector, flat file). Schemas, refresh cadence, and the persistent property identifier are consistent across products and delivery channels. All datasets are AI-ready — standardised schemas, consistent column naming across all ten provinces, and native MCP delivery for AI agents. No MLS membership, real estate license, or board affiliation is required to access BrightCat data.

BrightCat Listings

Weekly lifecycle tracking across 5.8M+ Canadian residential properties. Every listing, every price change, every status transition — captured at the property level since 2014.

Properties tracked5,819,621 unique residential
Columns per record135+
Lifecycle statesNEW, PRICE CHANGED, EXTENDED, DROPPED, RELISTED, SOLD, EXPIRED, WITHDRAWN
Key fieldsAsking price, days on market, property type, bedrooms, bathrooms, sqft, lot size, cumulative price change, original price, price/sqft, annual taxes, parking
HistoryContinuous weekly since 2014 (12 years)
CoverageAll 10 Canadian provinces
Use casesPre-mover acquisition, pricing intelligence, market monitoring, AVM enrichment, CRM lead triggers

Product details → · Full schema →

BrightCat Sold

Canadian residential sold transactions with full listing-to-sale history. Every sold event is linked to its original listing record through the persistent property identifier.

Total sold events899K+ events across 751K unique properties
Columns per record221
Key fieldsSold price, sold date, listing price at time of sale, days on market to sale, price change from listing to sold, property attributes
LinkagePersistent property identifier links sold events to listing lifecycles across relists and agent changes
HistoryContinuous since 2014
Use casesAppraisal, comparable analysis, HPI construction, mortgage portfolio monitoring, mark-to-market

Product details → · Full schema →

BrightCat Rentals

Canadian residential rental listings with national coverage. Unit-level tracking of asking rents, availability, and relisting patterns.

Unique properties205K+ unique rental properties
Active per week~39K active listings/week
National median rent$2,300/month (current)
Weekly snapshots233 weekly tables from July 2021 to present
CoverageAll 10 Canadian provinces
Use casesRental market analysis, investment property tracking, supply-side research, cap rate monitoring

Product details →

BrightCat Commercial

Canadian commercial properties across sale and lease tracks in a unified view. Dual-listing detection flags properties simultaneously marketed for both sale and lease.

Unique properties297,622 unique commercial
Active per week~84K active/week (58K sale + 26K lease)
Dual-listed10,092 properties simultaneously listed for sale and lease
Columns105 (unified master) / 114+ (schema)
Property classesOffice, industrial, retail, multifamily, land, specialty
Use casesCommercial transaction detection, dual-listing intelligence, investment analytics, lender collateral monitoring

Product details → · Full schema →

BrightCat Core

Unified property-level enrichment combining all BrightCat datasets. Includes the Canadian Home Price Index built on the repeat-sales methodology.

Repeat-sale pairs194,167 verified pairs
HPI baseJanuary 2014 = 100
Current national index169.7
Delivered asRaw pair table (both sale prices, both dates, persistent property ID) — not a composite index number
EnrichmentCross-product joins, investment property flags, lifecycle completeness scoring
Use casesAVM training, multi-asset analytics, enterprise risk, research, diversified portfolio management

Product details → · HPI schema →

BrightCat PreMovers

Pre-mover intelligence identifying Canadian households before they relocate. Signals are based on observed listing activity, not predictions or statistical models.

Signal typeObserved listing activity (not modeled/predicted)
Lead time4–12 weeks before the move
Delivery cadenceWeekly (every Sunday)
GranularityProperty-address level across all 10 provinces
HistoryContinuous since 2014 (12 years)
Use casesTelecom customer acquisition, insurance retention, mortgage discharge flagging, direct-marketing triggers

Product details →

Delivery

All six datasets are available through three delivery paths. Schemas, refresh cadence, and the persistent property identifier are identical across channels.

Path Best for Auth
Snowflake MarketplaceAnalytics, dashboards, SQL joins to internal dataSnowflake native
MCP ConnectorAI agents, conversational analytics, ClaudeOAuth 2.0
Flat fileDatabricks, BigQuery, on-prem, regulated workloadsSFTP credentials

Sample query

-- Quick overview: active market by province (Snowflake)
SELECT province,
       COUNT(*) AS active_listings,
       ROUND(AVG(asking_price), 0) AS avg_asking,
       ROUND(AVG(days_on_market), 0) AS avg_dom
FROM BRIGHTCAT_LISTINGS.PRODUCT.listings_weekly
WHERE listing_status IN ('NEW', 'PRICE CHANGED', 'EXTENDED')
  AND file_date = (SELECT MAX(file_date)
                   FROM BRIGHTCAT_LISTINGS.PRODUCT.listings_weekly)
GROUP BY province
ORDER BY active_listings DESC;
Six datasets. Three delivery paths. One pipeline. The same persistent property identifier runs through every product — join across datasets, query across delivery channels, and build on twelve years of continuous Canadian property intelligence.

Frequently asked questions

What Canadian property datasets does BrightCat offer?
Six datasets: Listings (5.8M+ residential properties tracked weekly), Sold (transaction events with listing-to-sale history), Rentals (national rental listings since July 2021), Commercial (297K+ properties with dual-listing detection), Core (unified enrichment with 194K+ repeat-sale HPI pairs), and PreMovers (weekly pre-mover intelligence). All datasets share the same pipeline and persistent property identifier.
How is BrightCat data delivered?
Three delivery paths: Snowflake Marketplace (Secure Data Share into the client's environment), MCP Connector (AI-native access for Claude and compatible agents), and flat-file delivery (Parquet or CSV via SFTP). All paths share the same underlying pipeline, schemas, and weekly refresh cadence.
How many columns does BrightCat Listings have?
135+ columns per property record, including listing price, days on market, property type, bedrooms, bathrooms, square footage, lot size, listing status, cumulative price change, original price, price per square foot, annual property taxes, parking type, and parsed address components.
Can I evaluate BrightCat data before licensing?
Yes. Every Snowflake Marketplace listing includes a sample schema that can be queried before any commercial commitment. The MCP Connector supports the same sample tier. Evaluation is zero-friction.
How far back does BrightCat data go?
The pipeline has operated continuously since 2014 with weekly refresh. Listings and Sold cover 12 years of continuous history. Rentals coverage begins July 2021. Commercial pipeline data is available from 2024 forward with historical reconstruction.
What is the persistent property identifier?
BrightCat assigns a stable identifier to each physical property, reconciled across relists, address variations, agent changes, and listing number reassignments. This is what makes it possible to track a single property across its full lifecycle — something that fragmented MLS data or listing-number-based systems cannot do.
Do I need a real estate license or MLS membership to access BrightCat data?
No. BrightCat data is commercially licensed enterprise data. No MLS membership, real estate license, or board affiliation is required. Access is available to any qualified enterprise buyer via Snowflake Marketplace, MCP Connector, or flat file delivery.
Is BrightCat data AI-ready?
Yes. All six datasets are structured for direct ingestion by AI systems: standardised schemas, consistent column naming across all provinces, weekly cadence, and native MCP delivery for AI agents. The data is used by enterprise AI teams for model training, RAG pipelines, and agent grounding without additional cleaning or transformation.

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