mapslegalanti-bot

Maps Scraping: Google Maps vs Waze Data — What You Can Legally Extract and How

sscraper

2026-01-23

10 min read

Technical & legal guide to extracting POIs, routes and live traffic from Google Maps vs Waze — with proxy, rate-limit best practices and a Playwright example.

Hook: Why maps scraping keeps you up at night (and how to fix it)

If your product depends on reliable POIs, accurate route geometry or near-real-time traffic incidents, you face three recurring headaches: platforms aggressively block scraping, legal exposure when you extract user-contributed data, and minefield-level complexity building resilient proxy + rate-limiting infrastructure. In 2026 these problems sharpened — anti-bot ML, browser fingerprinting, and stricter privacy regimes make naive scraping unsustainable.

Executive summary — what to act on today

Use official APIs first. Google Maps Platform and Waze for Cities provide legal, reliable feeds for POIs, routes and incidents; they cost money but save risk and engineering time.
Know what scraping actually buys you. Scraping UI surfaces can reveal internal endpoints and fresher user reports but comes with higher legal and technical costs.
Design rate limits and proxy strategy intentionally. Global projects need geolocated residential proxies, sticky sessions and token-bucket rate limiting with jitter.
Comply with privacy & TOS. Treat scraped user-contributed reports as potentially personal data under GDPR/CPRA and keep an audit trail of sources and consent status. Also budget appropriately — budget for API access and vendor fees beats surprise compliance costs.

The 2026 landscape: trends that matter for maps data extraction

Since late 2024 and into 2025–2026 the market hardened. Two trends changed how you must approach maps scraping:

Anti-bot sophistication — server-side ML and client-side fingerprinting (canvas, WebGL, TLS ClientHello fingerprinting) are now mainstream. CAPTCHA providers offer enterprise protection tied to browser signals.
Platform monetization & enforcement — major map providers moved to API-first monetization and more active enforcement of TOS, including automated bot detection and account-level throttles.

Google Maps vs Waze — what each platform is built for (and how that affects scraping)

Google Maps (2026)

Google Maps remains the broad, canonical source for POIs, geocoding, imagery and route planning. The Google Maps Platform exposes the Places API (POIs), Directions API (routes), Roads API and Traffic layer via SDKs and REST endpoints — these are the supported, licensed ways to access data.

Key characteristics:

Authoritative POIs. Rich metadata: names, IDs, types, hours, reviews.
Managed traffic signals. Traffic congestion is provided via Traffic Layer and is also embedded in Directions API responses.
Strict TOS. Scraping Maps UI or tile images typically conflicts with Google’s terms and copyright; Google has invested in detection and takedown.

Waze (2026)

Waze is optimized for crowd-sourced, near-real-time traffic and incident reporting. Since its acquisition by Google, Waze runs two important programs relevant to data access: the Waze for Cities (partner program providing live feeds and SDKs) and public Waze app UI that displays live incidents submitted by users.

Key characteristics:

Realtime incident signals. User reports (accidents, hazards, slowdowns) are often fresher than aggregated traffic layers.
Community-sourced noise. Reports are high-value but vary in quality and may include personal identifiers in comments.
Legalized access via programs. Waze for Cities gives you an authorized incident feed; scraping the app UI is high-risk and may be against program rules and privacy expectations.

Legality & compliance: what you can and shouldn’t extract

Short answer: Prefer APIs and partner programs; only collect from UI scraping after legal review and when it’s not expressly forbidden. This section gives practical boundaries (not legal advice).

POIs

Google: Use the Places API. Scraping the Maps UI for POIs is commonly a TOS violation and can trigger copyright/time-based enforcement. Cached POI lists must follow Google’s caching rules and attribution requirements.
Waze: Waze does not position itself as a POI master. For POIs, rely on Google or third-party POI datasets. Scraping POI-like overlays in Waze is brittle and likely violates terms.

Routes & geometry

Google: Use the Directions API and Roads API for snapped geometry. Exporting or republishing raw route geometry beyond internal use can be restricted.
Waze: Route suggestions in Waze are dynamic and tied to their routing engine; Waze for Cities partnership gives access to incident feeds, not necessarily route snapshots. Scraping route visuals may violate terms and is fragile.

Traffic incidents & live congestion

Waze: The platform’s strength. Apply to Waze for Cities for an authorized incidents feed; that’s the safest path to near-real-time reports.
Google: Live congestion is available via the Traffic Layer and the Traffic Model in Directions API. The Google Places / Directions responses can include delay estimates.
Scraping live incident overlays from either UI is both legally risky and technically brittle — prefer partner feeds.

Privacy and personal data

User-submitted reports can contain personal data. Under GDPR, CPRA and similar laws, you must:

Justify lawful basis for processing (e.g., legitimate interest with documented DPIA).
Minimize data (store only fields you need), and mask or remove identifiers.
Keep audit logs showing data provenance and retention schedules — tie these logs into your privacy incident playbook and retention policies.

Practical rule: If you need POIs, routes, congestion for commercial use, budget for API access — it’s cheaper than compliance and legal risk.

When scraping still makes sense (and how to reduce risk)

There are legitimate reasons to scrape: research, competitive monitoring in jurisdictions with weaker API access, or discovering internal endpoints to optimize integration. If you choose to scrape, follow these guardrails:

Document your legal analysis. Keep copies of terms, notices, robotstxt and legal counsel opinions.
Prefer public data. Scrape only what’s publicly visible without authentication, and avoid user profile pages or private content.
Rate-limit aggressively. Match human behavior and stay under API-like thresholds.
Respect robots.txt where feasible. It’s not a legal shield but shows good-faith behavior.
Monitor for blocks and back off. Implement exponential backoff with jitter and stop on legal takedown notices — tie your playbooks into an outage-ready incident plan.

Proxy and rate-limiting playbook (production-ready)

Successful maps scraping at scale requires a robust proxy architecture and deterministic throttling. Below is a battle-tested setup.

Proxy strategy

Prefer residential / ISP proxies for heavy UI scraping — they look like real users and reduce block rates. For architecture patterns and cost-aware edge deployments see edge-first, cost-aware strategies.
Use geo-located pools — requests must originate from the region you’re querying (maps often respond differently by locale).
Implement sticky sessions for flows that require consistent cookies and session state (use session affinity per proxy).
Rotate TLS fingerprints where possible — newer anti-bot stacks fingerprint the TLS ClientHello; tools like modern-tls or managed proxy providers offer fingerprint rotation. Pair this with your security stack best practices from zero-trust security guidance.
Fallback to scalable datacenter proxies only for low-frequency, high-volume tasks and API scraping where fingerprinting risk is low.

Rate limiting & politeness

Implement a two-layer rate-limiter:

Global token bucket — limits requests per second across all workers for a provider (e.g., 5 reqs/s).
Per-IP session limiter — smaller bucket per proxy session (e.g., 1–2 reqs/s).

Also add exponential backoff with jitter on 429/5xx and an adaptive failure detector that reduces concurrency when errors spike — combine this with chaos-style failure testing such as chaos testing for access policies to validate behavior under bans.

Detection & telemetry

Track response headers and body patterns that indicate blocking (e.g., captcha challenge pages, “unusual traffic”) — feed these signals into a centralized observability pipeline (observability for hybrid/edge).
Capture and centralize browser-level signals (JS challenge duration, resource loads) to inform routing decisions.
Alert on IP-level bans and rotate to cold pools when bans occur. Keep ban analytics and cost telemetry so you can spot anti-bot thresholds and the real cost of evasion.

Technical example: Playwright approach for extracting POIs & incidents (Node.js)

This example demonstrates a lawful-scraping-first mindset: identify a public UI XHR endpoint (for research), capture structured JSON, and respect rate limits. Remember: prefer APIs where possible. The snippet focuses on operational best practices — proxy usage, session stickiness, header hygiene, and request interception.

What this snippet does

Starts Playwright with a geo proxy and reasonable user agent
Intercepts network responses to capture internal JSON (search/incident endpoints)
Implements per-session delay and basic exponential backoff

// Node.js (Playwright) - conceptual snippet, not a turnkey scraper
const { chromium } = require('playwright');
const PROXY = { server: 'http://residential-proxy:8000', username: 'u', password: 'p' };
const USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36';

async function runSession(query, region) {
  const browser = await chromium.launch({ headless: true, args: ['--no-sandbox'] });
  const context = await browser.newContext({
    proxy: PROXY,
    userAgent: USER_AGENT,
    viewport: { width: 1366, height: 768 },
    locale: region.locale || 'en-US'
  });

  const page = await context.newPage();

  // Intercept network responses looking for JSON endpoints
  page.on('response', async res => {
    try {
      const url = res.url();
      if (/\/search|\/geocode|\/incidents|\/nearby/i.test(url)) {
        const ct = res.headers()['content-type'] || '';
        if (ct.includes('application/json')) {
          const json = await res.json();
          // Persist JSON to structured store for analysis
          console.log('captured', url, Object.keys(json || {}).slice(0,5));
        }
      }
    } catch (e) { /* ignore parsing errors */ }
  });

  // Navigate slowly to mimic human behaviour
  await page.goto('https://www.google.com/maps', { waitUntil: 'networkidle' });
  await page.waitForTimeout(1200 + Math.random() * 800);

  // Example: type in a search box and wait for results
  await page.fill('input[aria-label="Search Google Maps"]', query);
  await page.keyboard.press('Enter');
  await page.waitForResponse(r => /search\/rpc|place\/details/i.test(r.url()), { timeout: 10000 })
    .catch(()=>{});

  // Respect politeness: wait and close
  await page.waitForTimeout(2000 + Math.random() * 2000);
  await context.close();
  await browser.close();
}

// usage
(async () => {
  try {
    await runSession('coffee shops near 94107', { locale: 'en-US' });
  } catch (e) { console.error(e); }
})();

Notes on the snippet:

Do not hardcode high concurrency; wrap runSession in a worker pool with token-bucket limits and consider techniques from our layered caching case study to reduce API and UI calls.
Intercepted JSON often contains internal IDs — do not republish them without verifying license rights.
Use a persistent store and write provenance metadata (timestamp, proxy IP, TOS snapshot).

Data hygiene and downstream considerations

Once you have POIs, routes and incidents, treat them as production signals:

Normalize canonical IDs. Map scraped POIs to canonical place IDs when possible (Places API IDs) to deduplicate.
Score freshness. Assign TTLs based on source: Waze incident report TTLs are short (minutes), Google Places are longer-lived.
Mask PII and log provenance. Never surface user comments or handles without consent; hash identifiers and keep the original only in an encrypted audit trail.
Rate-limit consumers. Provide downstream teams cached, aggregated endpoints rather than raw scraped outputs to control usage and remain within licensing constraints. Instrument everything and feed metrics into a micro-metrics pipeline so product teams see the real cost of data freshness.

Operational checklist before you scrape maps in production

Confirm business need that justifies scraping vs API costs.
Run a legal/TOS review and document sign-off.
Choose proxy provider and test fingerprint stability across regions.
Implement layered rate limits and exponential backoff.
Enforce data minimization and retention policies.
Maintain an incident response plan to honor takedown notices and implement rapid removal — integrate with your privacy incident playbook and outage actions.

Future predictions (2026–2028) — prepare accordingly

More platform APIs with tiered pricing. Expect providers to offer more granular, higher-priced real-time traffic and incident feeds.
AI-driven anti-scraping defenses. ML models will increasingly fingerprint behavior patterns across sessions; mimicry alone will not suffice.
Regulatory scrutiny. Privacy rules will tighten around user-contributed location reports — plan for more consent and data subject rights management.
Rise of data partnerships. Many vendors will opt for formal data partnerships as the cleanest path to scale.

Concrete takeaways

First choice: official APIs and partner programs (Waze for Cities, Google Maps Platform). These reduce legal and operational risk.
If scraping, design for resilience and compliance. Residential proxies, sticky sessions, token-bucket rate-limiting, and privacy controls are mandatory.
Instrument everything. Collect provenance, fingerprint changes, and ban telemetry so you can adapt quickly.
Budget for compliance. Buying authorized access often costs less than engineering, monitoring, and legal risk over time. See practical billing and budgeting notes in billing platform reviews.

Disclaimer

This article provides practical engineering and compliance guidance but does not constitute legal advice. Consult a qualified attorney for jurisdiction-specific legal interpretation and to assess contract/TOS risk.

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