The definitive Google Trends automation engine with over 10,600+ successful runs. Extract breakout queries, historical interest curves, regional heatmaps, and real-time trending searches without IP bans.
{
"keyword": "autonomous ai agents",
"timeframe": "today 12-m",
"geo": "US",
"interestOverTime": [
{
"date": "2026-01-01",
"value": 34
},
{
"date": "2026-06-01",
"value": 68
},
{
"date": "2026-09-01",
"value": 100
}
],
"relatedQueries": [
{
"query": "best autonomous ai agent framework",
"value": "Breakout"
},
{
"query": "ai agents enterprise use cases",
"value": "+450%"
}
],
"topRegions": [
{
"region": "California",
"value": 100
},
{
"region": "Washington",
"value": 88
},
{
"region": "New York",
"value": 82
}
],
"scrapedAt": "2026-09-25T14:30:00Z"
}
Built specifically for high-throughput enterprise pipelines with zero credential leakage.
Real-time trends, interest over time (historical), interest by region (sub-regions & cities), related queries, and related topics.
Captures surging search queries marked as Breakout (+5000% growth) before they reach peak mainstream saturation.
Output is automatically normalized into clean rectangular rows, ready for immediate import into Excel, BigQuery, or Power BI.
Built-in residential proxy rotation with zero compute time billing. Only pay for successful events extracted.
Trigger extractions via the official Apify Client or standard REST endpoints.
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"searchTerms": ["artificial intelligence", "quantum computing"],
"timeframe": "today 3-m",
"geo": "US",
"extractRelatedQueries": True,
"extractRegionalInterest": True
}
run = client.actor("unitbytes/google-trends-scraper-api").call(run_input=run_input)
for record in client.dataset(run["defaultDatasetId"]).iterate_items():
print(record["keyword"], record["date"], record["value"])
Libraries like pytrends are severely rate-limited by Google (HTTP 429) within minutes. UnitBytes manages residential proxy rotation and request orchestration to guarantee 99.9% uptime at scale.
Yes. Pass up to 5 comparison terms simultaneously to receive normalized relative search volume curves across all queries.
All official Google timeframes: past hour, past 4 hours, past day, past 7 days, past 30 days, past 90 days, past 12 months, past 5 years, or full history from 2004 to present.
Queries experiencing exponential growth (+5000% increase) are explicitly tagged with Breakout for instant alert triggers.
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Our data engineering team provides private cluster deployments, custom webhook integrations, continuous schema monitoring, and high-frequency delivery directly to BigQuery, Snowflake, or AWS S3.
Start running immediately on UnitBytes Cloud with zero infrastructure setup, or contact our engineering team for dedicated S3/BigQuery delivery pipelines.