We extract public matrimonial profiles, community distributions, educational backgrounds, and partner preferences from Jeevansathi. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Basic Demographics objects from jeevansathi.com. All fields typed and schema-versioned.
"profile_id": "JS839201A", "age": 28, "height_cm": 165, "gender": "Female", "marital_status": "Never Married", "religion": "Hindu", "caste": "Brahmin", "mother_tongue": "Hindi", "location_city": "Delhi"
| # | profile_id | age | height_cm | gender | marital_status | religion |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Education & Career objects from jeevansathi.com. All fields typed and schema-versioned.
"profile_id": "JS839201A", "highest_education": "PG", "pg_degree": "MBA/PGDM", "occupation": "Marketing Professional", "income_bracket_inr": "15,00,000 - 20,00,000", "working_location": "Gurgaon", "professional_sector": "Corporate", "ug_degree": "B.Tech"
| # | profile_id | highest_education | ug_degree | pg_degree | college_name | occupation |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Lifestyle & Family objects from jeevansathi.com. All fields typed and schema-versioned.
"profile_id": "JS839201A", "diet": "Vegetarian", "smoking_habit": "No", "drinking_habit": "Occasionally", "family_type": "Nuclear", "family_values": "Moderate", "father_occupation": "Retired", "siblings_count": 2
| # | profile_id | diet | smoking_habit | drinking_habit | family_type | family_values |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Partner Preferences objects from jeevansathi.com. All fields typed and schema-versioned.
"profile_id": "JS839201A", "pref_age_min": 28, "pref_age_max": 32, "pref_height_min_cm": 170, "pref_marital_status": "Never Married", "pref_religion": "Hindu", "pref_education": "PG/Masters", "pref_income_min_inr": "20,00,000"
| # | profile_id | pref_age_min | pref_age_max | pref_height_min_cm | pref_height_max_cm | pref_marital_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Account Metadata objects from jeevansathi.com. All fields typed and schema-versioned.
"profile_id": "JS839201A", "membership_tier": "eAdvantage", "profile_managed_by": "Self", "verification_status": "Aadhaar Verified", "photo_count": 4, "profile_created_date": "2023-11-14", "last_active_date": "2024-02-10", "profile_url": "https://www.jeevansathi.com/profile/view/JS839201A"
| # | profile_id | profile_created_date | last_active_date | membership_tier | profile_managed_by | verification_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Jeevansathi scraper navigates community filters, paginated search results, and complex profile structures to extract clean demographic and preference datasets.
Capture age, height, religion, caste, education, occupation, and income brackets from public profiles.
Map user bases across states, cities, and specific communities to analyse regional marriage trends.
Extract granular details on undergraduate degrees, post-graduate qualifications, and professional sectors.
Extract strict and flexible matching criteria including age ranges, height preferences, and acceptable castes.
Navigate complex categorisations of religion, caste, and sub-caste specific to the Indian matrimonial market.
Track NRI profiles, citizenship status, and preferred relocation cities across the global user base.
Extract dietary preferences, drinking habits, and smoking status correlated with demographic segments.
Run continuous pipelines that only output updated profiles, reducing storage costs and downstream processing.
Bypass rate limits and IP blocks using residential proxies and human-like request pacing.
Brief in. Clean data out.
Provide target communities, geographic regions, or specific filters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for jeevansathi.com.
Schema validation, null-rate checks, and sample profile data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Matrimonial sites restrict scraping to protect user data and server load. We handle the technical barriers so you get reliable demographic data.
Jeevansathi aggressively blocks data centre IPs. We route requests through verified Indian residential proxies to maintain uninterrupted access to public search directories.
Search results are capped at a specific number of pages. We mathematically divide search spaces using granular filters (age, height, specific sub-castes) to extract the entire catalogue without hitting pagination walls.
Profile layouts change based on the user's completion rate and privacy settings. Our extraction logic uses multiple fallback selectors to ensure high field-fill rates regardless of the profile template.
Certain community pages require specific session cookies to render correctly. We maintain active browser sessions via Playwright to access these regional directories.
We hash profile metadata on each run. If a user updates their occupation or partner preferences, we emit only the changed record, saving compute and storage costs.
Analyse demographic trends, average marriage ages, and shifting community preferences across different Indian states.
Sociologists and economists study correlations between education, income brackets, and caste preferences in modern marriages.
Rival platforms track user base growth, regional penetration, and feature adoption across the Jeevansathi ecosystem.
Wedding vendors, real estate firms, and jewellers size specific demographic audiences to optimise ad spend.
Data science teams train recommendation engines and matching algorithms using historical partner preference data.
Correlate self-reported income brackets with educational attainment and geographic location to track middle-class wealth distribution.
"Jeevansathi holds the most structured demographic and socio-economic dataset in India, but extracting it requires navigating strict rate limits and complex community hierarchies."
Matrimonial platforms deploy aggressive rate limiting and session validation to prevent mass scraping. DataFlirt manages the residential proxy rotation, request throttling, and pagination logic so your team receives clean, normalised demographic data without managing the extraction infrastructure.
Everything supported by our jeevansathi.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across IN regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About jeevansathi.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available demographic information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated profile data. We do not extract personal contact information, circumvent authentication walls, or violate user privacy. Clients should review Jeevansathi's ToS and consult legal counsel for specific use cases.
Jeevansathi caps search results to a specific number of pages. We bypass this by programmatically intersecting multiple granular filters (e.g., age 25 + height 160cm + specific sub-caste) to create thousands of small search queries, ensuring we extract the entire directory without hitting the limit.
No. Phone numbers and email addresses are gated behind paid memberships and user consent mechanisms. We only extract demographic and preference data visible on public profile layouts.
Yes. We can target specific linguistic, religious, or caste-based directories, ensuring the data is mapped exactly to your required demographic segments.
Full catalogue refreshes typically complete within a 48-hour window depending on the target volume. For specific community tracking, we can run daily diff pipelines to capture new registrations and profile updates.
Our selector strategy uses multiple fallback chains per field. If Jeevansathi updates their DOM structure, our pipeline detects the schema drift, alerts our ops team, and falls back to secondary extraction methods (like structured JSON-LD data) to maintain pipeline integrity.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off demographic dump or continuous tracking across specific communities - we scope, build, and operate the pipeline. Tell us what you need.
