Best Google Trends Alternatives in 2026: APIs & Scrapers

Google Trends is still the reference point for search-interest data, but it is no longer the only option. Google announced an alpha version of the Google Trends API on 24 July 2025, which means the official programmatic path exists but is new. If what you need is a stable production interface today, an automation layer, or trend signals that are not search data at all, you are looking at alternatives.

This guide compares the main Google Trends alternatives by workload: a maintained Python client, Apify scrapers, a Wikipedia-based trend index, a proprietary trends API, a browser extension, and TrendsAGI, our own real-time trend intelligence platform. It tells you which to pick, what each costs where a public rate exists, and what the vendors do not disclose.

Which alternative should you choose?

• If you need to keep an existing Python build working after a pytrends dependency retires, choose pytrends-alternative.
• If your high-volume keyword research keeps hitting Google rate limits and you want automatic retries, choose the Dataspace Apify Google Trends Scraper.
• If you want Google Trends fields such as by-region, by-city, rising queries and Trending Now volumes, choose the Hiver Apify scraper.
• If you want trend signals with no Google scraping at all, choose the Kanto Labs Wikipedia topic-trends actor.
• If you want keyword popularity over time from a proprietary algorithm rather than Google data, evaluate the DataForSEO Trends API.
• If you want trend numbers inline while you search, choose the Treendly Chrome extension.
• If you need social-platform trend detection with AI explanations feeding a marketing workflow or an AI agent, choose TrendsAGI.
• Stay with Google Trends if you only need exploratory research in the browser, you are fine with the free UI, and you do not yet need a programmatic feed or any guarantee about refresh cadence.

Why people look for alternatives

The pull away from Google Trends is mostly about programmatic access, not about the exploration UI. Google Trends offers an Explore view of the most-searched terms and topics by location, time range, category and Google product, per Google for Developers. That covers a lot of research work.

What it does not cover until recently is automation. Google announced the alpha version of the Google Trends API on 24 July 2025. Alpha means access is new, and the research does not confirm general availability, access terms or whether it is free, so treat production dependence as a risk to verify with Google directly. Apify frames the same gap in its own words, attributing the wave of alternatives and managed clients to Google's limited official API access.

The result is a fragmented market with very different products underneath: some scrape Google, some call Google through a managed client, some use Wikipedia pageviews, and some use proprietary algorithms. Two of them measure something that is not Google search interest at all.

Code example: a real trend API in Python

Before the vendor-by-vendor list, here is what a maintained API client looks like in practice. This uses the TrendsAGI Python SDK, with the key read from an environment variable and explicit handling for both a failed response and pagination:

import os
from trendsagi import TrendsAGIClient

client = TrendsAGIClient(api_key=os.environ["TRENDSAGI_API_KEY"])

page = 1
seen = []
while True:
    batch = client.get_trends(category="Technology", sort_by="velocity", limit=50, page=page)
    trends = batch.get("trends", [])
    if not trends:
        break
    for t in trends:
        seen.append(t["id"])
        insights = client.get_ai_insights(t["id"])
    page += 1

print(len(seen), "trends collected")

Velocity in TrendsAGI is a measured snapshot rate of posts per hour, not a forecast and not a unique-user count, and recommendation confidence measures evidence completeness rather than the probability that a campaign will succeed. Keep those definitions in mind whenever you compare its numbers with Google's 0–100 index, because they are different scales.

pytrends-alternative

Best for: teams retiring an archived pytrends script. It is a maintained Python client that re-exports TrendsAPI, AsyncTrendsAPI and TrendsAPIError from the official client, so an existing request shape keeps working.

Main trade-off: it is a client, not a data source, so your reliability is still bound to whatever sits behind it. The research does not confirm whether its claimed 30+ other sources include non-Google data or what those sources are. Pricing, rate limits, plan tiers and support channels are not publicly listed for it.

Moving from Google Trends: the migration is mostly mechanical if your code already uses pytrends, since the API surface is the same. Budget time for re-verifying error handling.

Apify Google Trends scrapers

Best for: teams that need Google-shaped fields without building their own scraper. The Hiver actor returns interest over time, by region, by city or US metro, rising related queries, keyword comparison and Trending Now searches by country with volume, and charges $1.90 per 1,000 search terms and $0.80 per 1,000 trends, with empty or refused terms free. The Dataspace actor performs automatic retries on Google rate limits and is priced from $1.80 per 1,000 keywords or trends.

Main trade-off: these are unofficial scrapers, so blocking and refusal risk is real. Dataspace's retries help but do not remove that exposure. Billing is disclosed for these two actors; accuracy, latency and refresh cadence relative to Google Trends are not.

Moving from Google Trends: expect to map Google's 0–100 index onto the actor's output rather than carry your thresholds across unchanged. Only Hiver's published terms state that refused terms are free, so ask other vendors what happens on failure before you commit to volume.

Kanto Labs Wikipedia topic trends

Best for: analysts who want to avoid scraping Google entirely. The actor produces 0–100 interest-over-time topic trends from official Wikipedia pageview data covering 2015 to yesterday, priced from $3.00 per 1,000 topics analyzed.

Main trade-off: Wikipedia pageviews are not Google searches. Interest over time exists, but do not expect Google's region, city or related-query breakdowns.

Moving from Google Trends: this is a data-source change, not a migration. Rebuild any baseline or threshold you set against Google's index.

DataForSEO Trends API

Best for: developers who need keyword popularity over time by region without Google data. It uses a proprietary algorithm, so it is not a Google Trends mirror.

Main trade-off: a proprietary index cannot be validated against Google, and the research sheet gives no pricing, rate limits, plan tiers or support details for it. Those are not publicly listed.

Moving from Google Trends: treat every trend line as a new series and recalibrate.

Treendly Chrome extension

Best for: an SEO practitioner who wants trend signals inline while searching. It shows a sidebar with a 5-year trend chart, growth-pace badge, monthly search volume and category/region data on search pages.

Main trade-off: it is a reading aid, not an API or a pipeline. Pricing and data provenance are not publicly listed in the research.

TrendsAGI (our own product)

Disclosure: TrendsAGI is published by the team writing this guide.

Best for: marketers, growth and paid-media teams, creators, newsrooms, PR and operations teams, and developers building AI agents. It detects topics gaining attention on social platforms, measures velocity as posts per hour from stored snapshots, and adds AI insights covering summary, key themes, sentiment, audience and marketing angles. Outputs include evidence-backed recommendations, crisis alerts and watchlist alerts.

Main trade-off: it is not a Google search-volume index, so it will not answer a question phrased purely in monthly search volume. Non-search sources are its point, not a gap.

What moving involves: authentication with the header X-API-Key: <key> or Authorization: Bearer <key>, against base URL https://api.trendsagi.com. Useful endpoints include GET /api/trends with sort_by=velocity|growth|volume|timestamp|name, GET /api/trends/{id}/ai-insights, GET /api/insights/search and GET /api/intelligence/recommendations. Install with pip install trendsagi. For agents, TrendsAGITools(client) is read-only by default and gains write tools with allow_writes=True; adapters cover OpenAI, Claude, LangChain and WebMCP. A hosted MCP server is available at https://api.trendsagi.com/mcp. Watchlist alerts use volume_threshold or percentage_growth conditions. Pricing is listed at trendsagi.com/subscription; confirm current terms there rather than relying on this article.

import os
from trendsagi import TrendsAGITools, TrendsAGIClient

client = TrendsAGIClient(api_key=os.environ["TRENDSAGI_API_KEY"])
tools = TrendsAGITools(client)

res = tools.call("list_trends", {"category": "Technology"})
if "error" in res:
    print("failed:", res["error"], res.get("detail"))
else:
    print(res["result"]["trends"][0]["id"])

Comparison at a glance

How to choose

• Write down your workload first: one-off research, a scheduled pipeline, or an in-browser check.
• Confirm the data source: Google search interest, Wikipedia pageviews, social posts, or a proprietary index. All four appear in the table and none are interchangeable.
• Check what happens to billed cost on a refused or empty term before you scale volume.
• Decide whether you need geographic granularity down to city or metro, and whether rising related queries are mandatory.
• Ask what is not disclosed: pricing, rate limits, support and refresh cadence. If a vendor cannot answer, plan a fallback.
• Test the free Google Trends alpha before paying for a scraper if all you need is light automation.

Frequently asked questions

What can Google Trends itself do today?

Per Google for Developers, it offers an Explore view of the most-searched terms and topics by location, time range, category and Google product. Google announced an alpha version of the Trends API on 24 July 2025. The gap is maturity and confirmed access terms, not the exploratory UI.

Which alternatives exist and what are they?

Four kinds: managed API clients such as pytrends-alternative, scrapers such as the Apify actors, proprietary indices such as DataForSEO and Wikipedia pageview data, and browser extensions such as Treendly.

Can I use these alternatives from Python, and is there a drop-in replacement for pytrends?

Yes. pytrends-alternative re-exports TrendsAPI, AsyncTrendsAPI and TrendsAPIError from the official client, which the research positions as the fit for an archived pytrends script.

How do the alternatives handle Google rate limits and refused queries?

The Dataspace Apify scraper performs automatic retries on Google rate limits. Hiver states that empty or refused terms are free, priced at $1.90 per 1,000 search terms and $0.80 per 1,000 trends. Other vendors' failure billing is not publicly listed.

What data can I actually get, and at what granularity?

Hiver returns interest over time, by region, by city or US metro, rising related queries, keyword comparison and Trending Now by country with volume. Kanto Labs returns 0–100 interest over time from Wikipedia pageviews, 2015 to yesterday.

What does each option cost per 1,000 terms or trends?

Public figures exist for three Apify actors: Kanto Labs from $3.00 per 1,000 topics analyzed, Hiver $1.90 per 1,000 search terms and $0.80 per 1,000 trends, Dataspace from $1.80 per 1,000 keywords or trends. Pricing for pytrends-alternative, DataForSEO and the Google alpha API is not publicly listed in the research, so verify directly.

How we researched this

Prepared by TrendsAGI Research. Facts checked on 24 October 2026 against the sources listed below.

We researched Google Trends and the other products named from their official sites, documentation and the sources below. Facts about them are documented there, not tested firsthand in a paid account. Facts about TrendsAGI, which publishes this page, come from its own product documentation.

We re-research and rewrite this page at least every four months; the updated date only changes when the facts are re-checked.

Sources

• Erste Schritte mit Google Trends | Google Search Central (Google for Developers) — developers.google.com
• Google Trends Scraper & API: pytrends Alternative (Apify) — apify.com

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