We extract K-12 profiles, college rankings, neighbourhood grades, demographic statistics, and student reviews from Niche. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for College Profiles objects from niche.com. All fields typed and schema-versioned.
"entity_id": "stanford-university-ca", "name": "Stanford University", "institution_type": "Private", "niche_grade": "A+", "acceptance_rate": 4.0, "net_price": 18279, "sat_range": "1500-1580", "enrollment": 7761
| # | entity_id | name | institution_type | niche_grade | acceptance_rate | net_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for K-12 Schools objects from niche.com. All fields typed and schema-versioned.
"entity_id": "stuyvesant-high-school-ny", "name": "Stuyvesant High School", "district": "New York City Geographic District No. 2", "grades_served": "9-12", "student_teacher_ratio": 21, "academics_grade": "A+", "public_private": "Public"
| # | entity_id | name | district | grades_served | student_teacher_ratio | diversity_grade |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Neighbourhoods objects from niche.com. All fields typed and schema-versioned.
"entity_id": "lincoln-park-chicago-il", "name": "Lincoln Park", "city": "Chicago", "state": "IL", "overall_grade": "A+", "housing_grade": "B+", "median_home_value": 542100, "median_rent": 1850
| # | entity_id | name | city | state | overall_grade | public_schools_grade |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from niche.com. All fields typed and schema-versioned.
"review_id": "rev_9823749", "entity_id": "stanford-university-ca", "author_type": "Alum", "star_rating": 5, "review_text": "Incredible academic environment with unparalleled resources.", "date_posted": "2025-11-12", "helpful_votes": 42
| # | review_id | entity_id | entity_type | author_type | star_rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Rankings objects from niche.com. All fields typed and schema-versioned.
"ranking_id": "best-colleges-2026", "title": "Best Colleges in America", "category": "Colleges", "year": 2026, "entity_name": "Yale University", "rank_position": 1, "niche_grade": "A+"
| # | ranking_id | title | category | year | entity_name | rank_position |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Niche scraper navigates Cloudflare protections, Next.js hydration states, and map-based pagination to extract structured education and neighbourhood data at scale.
Extract student-teacher ratios, diversity metrics, and academic grades for public and private schools across all districts.
Capture acceptance rates, application deadlines, SAT/ACT percentiles, and net price calculations for universities.
Pull granular A+ to F letter grades across academics, diversity, teachers, and college prep categories.
Extract median home values, rent costs, crime grades, and demographic breakdowns for geographic areas.
Paginate through student, alumni, and parent reviews with star ratings and helpful-vote counts.
Iterate through 'Best Colleges' or 'Best Places to Live' national and state-level ranking lists.
Extract racial, economic, and gender diversity statistics for student bodies and local populations.
Capture sticker price, average net price, and percentage of students receiving financial aid.
Bypass map-viewport limitations to extract complete entity lists within a geographic bounding box.
Brief in. Clean data out.
Provide target states, school districts, or college tiers. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, handle Cloudflare blocks, and map the Next.js data structures.
Schema validation, null-rate checks on critical fields like tuition, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Niche uses aggressive bot protection and complex frontend frameworks. Here is how we extract the data reliably.
Niche uses advanced bot protection. We route requests through ISP residential proxies and solve JavaScript challenges to maintain access and prevent IP bans.
Niche pages are React-rendered. We parse the underlying NEXT_DATA JSON payloads directly, bypassing DOM scraping for cleaner, faster, and more reliable extraction.
Niche caps visible pagination on large lists. We use targeted geographic and filter-based sub-queries to extract complete datasets without hitting hard limits.
Neighbourhood and school search relies on map viewports. We programmatically generate bounding boxes to sweep entire states systematically and capture all entities.
Not all schools report SAT scores or diversity metrics. Our pipelines use strict null-handling and schema validation to ensure downstream databases do not break when fields are absent.
EdTech vendors size addressable markets by mapping school districts, student populations, and technology budgets.
Firms correlate Niche neighbourhood grades and school ratings with property value appreciation models.
Consultants aggregate acceptance rates, SAT bands, and tuition costs to build predictive placement models.
Researchers analyse diversity statistics, funding disparities, and educational outcomes across public school districts.
Corporate relocation platforms integrate Niche grades to help employees evaluate neighbourhoods and school districts.
Tutors and test-prep companies target high-competition school districts based on academic grades and college-prep scores.
"Niche holds the definitive dataset on American education and neighbourhoods, but accessing that data programmatically requires navigating aggressive bot protection."
Extracting Niche data requires bypassing Cloudflare, parsing complex Next.js hydration states, and managing deep pagination across map-based interfaces. DataFlirt manages this infrastructure entirely, delivering normalised education and real estate data directly to your warehouse so your team can focus on analysis.
Everything supported by our niche.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 US 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 niche.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Niche is generally permissible under applicable law. DataFlirt targets only public, non-authenticated school, college, and neighbourhood data. We do not extract personal user data or circumvent authentication walls.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and automated solvers for JavaScript challenges to maintain access without triggering blocks.
Yes. We programmatically generate bounding boxes to sweep map-based search interfaces, ensuring we capture all entities within a state or city without hitting pagination limits.
Most clients opt for monthly or quarterly refreshes, as school and neighbourhood data changes slowly. Real-time extraction is available for specific ranking updates.
We can extract currently visible historical ranking lists on the platform. We also maintain a time-series archive for clients to track grade and rank changes over time.
Our smallest packages start at a defined list of 1,000 entities or a specific state's public school directory. Contact us with your scope for exact pricing.
Yes. We paginate through all available review pages, extracting the text, star rating, author type, and helpful vote counts for every review on a profile.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off database of US colleges or a continuous feed of real estate neighbourhood grades, we scope, build, and operate the pipeline. Tell us what you need.
