Financial Data APIs Compared: Alpha Vantage vs Polygon.io vs Yahoo Finance

This is not investment advice. We are comparing API quality, not recommending trading strategies. The code examples below fetch market data for demonstration purposes only. Past performance data does not predict future returns.

We pulled five years of daily OHLCV data for three symbols — SPY, AAPL, and BTC-USD — against three APIs that developers reach for when building stock screeners, dashboards, and backtesting pipelines. The goal was not to find the fastest or cheapest API in isolation. It was to see how each one handles the same query under its own constraints, and where the friction points hide for a developer who expects to run this query every day, maybe every hour, as part of a tool that someone else might depend on.

What each API actually covers — and what it does not

Alpha Vantage has the broadest asset coverage on paper: stocks, ETFs, forex, crypto, and a library of 50-plus technical indicators exposed as dedicated API endpoints. You can call the SMA endpoint and get a pre-computed simple moving average instead of downloading raw bars and calculating it yourself. That is a genuine time saver for quick prototyping. Everything runs through a REST API with JSON and CSV output. No WebSocket. No streaming. On the free tier, the coverage is there — you just cannot call it more than 25 times per day.

Polygon.io covers US equities, options, forex, and crypto, but its DNA is equities-first. The options chain data and Greeks are available on higher-tier plans. The API is modern REST plus WebSocket streaming on paid tiers. The documentation renders example responses inline, and the official SDKs in Python, Go, and JavaScript map directly to the API surface. If you want to iterate fast on US equities, the developer experience is the cleanest of the three.

Yahoo Finance is not an API product. It is a website that yfinance, a community-maintained Python library, reverse-engineers to extract structured data. There is no official endpoint, no API key, no SLA, and no support channel. The coverage is broad — stocks, ETFs, crypto, forex, fundamentals, news — because Yahoo Finance the website covers all of it. When yfinance works, it works well. When Yahoo changes their HTML structure, it breaks until the maintainers patch the parser, which tends to take a few days to a week. This happens roughly two to four times a year based on the library’s release cadence.

Five years of daily data: one query, three APIs

To compare what a developer actually experiences, we wrote a three-line fetch for each provider. The query was identical across all three: daily OHLCV for SPY, AAPL, and BTC-USD from January 2021 through January 2026.

# Alpha Vantage — REST API, JSON response, outputsize=full for deep history
requests.get(f"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol={ticker}&outputsize=full&apikey={key}")

# Polygon.io — REST, flat aggregates, date range embedded in URL path
requests.get(f"https://api.polygon.io/v2/aggs/ticker/{ticker}/range/1/day/2021-01-01/2026-01-01?adjusted=true&apiKey={key}")

# Yahoo Finance via yfinance — single call, returns pandas MultiIndex DataFrame
yf.download(["SPY", "AAPL", "BTC-USD"], start="2021-01-01", end="2026-01-01")

Alpha Vantage returned clean JSON with timestamps as dictionary keys and OHLCVOHLCV nested inside — a format that requires an extra unpacking step but is deterministic and well-documented. The outputsize=compact default returns only the last 100 data points; you need outputsize=full for anything deeper, which the free tier throttles server-side.

Polygon’s response came back as a flat array of arrays — compact, column-mapped, and fast to parse. Like CSV in JSON form. The date range is in the URL path rather than query parameters, and the response includes a resultsCount field that tells you exactly how many bars were returned before you parse them. This level of introspection is useful when you are debugging why a backtest has fewer data points than expected.

yfinance returned a pandas MultiIndex DataFrame directly — no API key, no JSON parsing, no column mapping. The trade-off is that you are trusting an unofficial scraper with no guarantees. During our test window in May 2026, all three queries completed without errors. But the yfinance approach has failed on us in the past during previous Yahoo HTML changes, and it will fail again.

Rate limits that shape your architecture

The rate limit model is the single most consequential difference between these three providers — more than pricing, more than data quality, because it determines what kind of pipeline you can build before you even think about monthly cost.

Alpha Vantage’s free tier limits you to 25 API calls per day. Not per hour. Not per minute. Per day. If your screener scans 100 tickers for one data point each, you get four tickers per day. The paid tiers remove daily limits and jump to 75 requests per minute at $49.99/month, which is workable for most side-project dashboards but steep for someone who just wants to pull end-of-day quotes for a personal portfolio.

Polygon’s free tier limits you to 5 requests per minute with no daily cap. If your script sleeps 12 seconds between calls, you can pull data for roughly 300 tickers overnight. This makes batch jobs possible on the free tier, just slow. The paid tiers scale from $29/month (Starter, unlimited calls, 15-minute delayed data) to $79/month (Developer, WebSocket streaming, 10 years of daily history) to $199/month (Advanced, real-time, tick-level data).

Yahoo Finance via yfinance has no documented rate limit because there is no official API. Our testing suggests that 2,000 requests per hour is roughly the safe window before Yahoo starts returning intermittent 429 errors or temporary IP blocks. But this is trial and error — there is no documentation to consult, and the threshold can change without notice.

Which API fits your project

We are not going to tell you that one API is the best. The answer depends on what you are building and how much you are willing to tolerate in exchange for free data.

For a personal stock screener that runs once a week and scans 500 tickers: yfinance is hard to beat on price. You get decades of historical daily data with one function call, and the DataFrame output drops directly into a pandas pipeline. The cost is reliability — you need a fallback plan for the weeks when Yahoo changes something and yfinance breaks. Keep a local CSV cache. It will save you.

For a side-project dashboard that refreshes end-of-day quotes for 10 to 50 symbols every evening: Polygon’s free tier at 5 requests per minute handles this comfortably. The JSON responses are consistent, the API key registration takes sixty seconds, and you can graduate to a $29/month plan if the project grows. The official Python SDK saves you from writing HTTP boilerplate.

For a production backtesting pipeline that needs intraday data, technical indicators, and guaranteed uptime: Alpha Vantage’s $99.99/month plan gives you real-time data, 150 requests per minute, and access to pre-computed indicators that reduce the code you write. The trade-off is the higher entry price and the lack of WebSocket streaming.

For a multi-asset prototype that needs forex and crypto alongside equities on the same free tier: Alpha Vantage is the only provider here that gives you all three asset classes at no cost — but you are limited to 25 calls per day. If your prototype needs to run more queries than that, you are either paying $49.99/month or switching to Polygon for per-minute throughput on equities only.