[Blog](https://scrapfly.io/blog) / [api](https://scrapfly.io/blog/tag/api) / [8 Best Financial Data APIs for Developers in 2026](https://scrapfly.io/blog/posts/best-financial-data-apis) # 8 Best Financial Data APIs for Developers in 2026 by [Mayada Shaaban](https://scrapfly.io/blog/author/mayada-shaaban-90143e67) Sep 17, 2026 18 min read [\#api](https://scrapfly.io/blog/tag/api) [\#data](https://scrapfly.io/blog/tag/data) [\#python](https://scrapfly.io/blog/tag/python) [\#scrapeguide](https://scrapfly.io/blog/tag/scrapeguide) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis "Share on LinkedIn") [ ](https://x.com/intent/tweet?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis&text=8%20Best%20Financial%20Data%20APIs%20for%20Developers%20in%202026 "Share on X") [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis "Share on Facebook") Summarize this article with [ ](https://chat.openai.com/?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis) [ ](https://claude.ai/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis) [ ](https://x.com/i/grok?text=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis) [ ](https://www.perplexity.ai/search/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis) [ ](https://www.google.com/search?udm=50&aep=11&q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fbest-financial-data-apis) A financial data API can return a clean JSON response and still be the wrong dependency. The "real-time" feed might cover one venue, the history might skip adjustments, or the license might block you from showing data to users. The eight providers below split that job differently, from prototyping and technical indicators to live streams and trading integration. Match the provider to the job, then verify its access method and rights before you build on it. [11 Best Web Scraping APIs, Libraries, and Crawlers for Developers in 2026Compare the best web scraping tools in 2026. Pipeline-based guide covering Scrapfly, BeautifulSoup, Playwright, Scrapy, and more for production scraping.](https://scrapfly.io/blog/posts/best-web-scraping-apis) ## Key Takeaways - **Pick by data job**, not feature count: prototypes, statements, streams, or trading. - **REST fits historical queries.** WebSocket feeds carry continuous updates. - **"Real-time" rarely covers every exchange** or the right to redistribute data. - **A free key proves connectivity**, not commercial or live-exchange entitlement. - **Massive, Finnhub, and Tiingo** pair REST with a WebSocket feed for live data. - **Tiingo spells out redistribution terms** most providers leave unstated. - **Scraping fills the gap** for public pages no licensed feed reproduces. **Get web scraping tips in your inbox**Trusted by 100K+ developers and 30K+ enterprises. Unsubscribe anytime. ## Which Financial Data API Is Best for Developers in 2026? Alpha Vantage fits prototypes and technical indicators. Financial Modeling Prep fits statements and filings. Massive fits live market streams and bulk files. Finnhub fits quotes plus company events. Twelve Data fits multi-asset time series. EODHD fits global historical coverage. Tiingo fits adjusted history with usage terms spelled out, and Alpaca fits applications that combine market data with trading systems. | Financial data API | Best for | Data emphasis | Access | |---|---|---|---| | Alpha Vantage | Prototypes + indicators | Multi-asset time series | REST, JSON, CSV | | Financial Modeling Prep | Statements + filings | Fundamentals + prices | REST, bulk | | Massive | Live market systems | Trades, quotes, ticks | REST, stream, files | | Finnhub | Company events | Quotes, news, estimates | REST, stream | | Twelve Data | Multi-asset apps | Time series + indicators | REST, stream, batch | | EODHD | Global history | EOD, fundamentals | REST, bulk, stream | | Tiingo | Adjusted research data | EOD, news, actions | REST, stream, CSV | | Alpaca | Data + trading | US equities, options, crypto | HTTP, stream, SDKs | This table maps workloads to providers. It isn't a measured ranking of speed, uptime, or accuracy. Exact prices and free-plan quotas change too often to print here. Check each provider's current pricing page before you commit a workload to it. [7 Best E-commerce Product Data APIs for Developers in 2026Seven e-commerce product data APIs compared by access model, from storefront catalogs and marketplace listings to seller-only operations feeds.](https://scrapfly.io/blog/posts/best-ecommerce-product-data-apis) ## How Were These Financial Data APIs Compared? This guide compares each API on what it returns, how it delivers that data, and what you're allowed to do with it. None of them gets a single numeric score. Five criteria drove the comparison: - **Data job**: live quotes and trades, historical bars, fundamentals, filings, news and events, indicators, or order execution. - **Freshness and venue**: real-time, delayed, and end-of-day data, plus which exchanges or feeds it covers. - **Delivery**: REST, WebSocket, batch requests, bulk files, JSON, and CSV. - **History and adjustments**: date depth, split and dividend adjustments, report dates, and whether fundamentals are point-in-time. - **Rights and adoption**: personal, internal commercial, display, and redistribution terms, plus self-serve testing versus sales-led access. This comparison reflects each provider's documentation as of September 14, 2026. No shared benchmark ran across these providers, so this guide doesn't score accuracy, latency, uptime, or reliability. Two recurring developer needs shaped why these criteria matter. Developers picking a stock data API often need real-time prices, volume, company reports, and industry categories in one dependency, not spread across several. Others building backtests report finding fundamentals data that's broken or restated. They want at least a decade of point-in-time history with bulk access, not a per-symbol crawl. Treat both as reader pain to plan around, not proof that any one provider solves it best. ## Project Setup The one runnable example below uses a single package, requests. Install it with pip: bash```bash pip install requests ``` Each numbered entry below documents that provider's current endpoints and authentication, and the Alpha Vantage entry includes the one working code sample. ## 1. Alpha Vantage: Best Financial Data API for Prototypes and Technical Indicators [Alpha Vantage](https://www.alphavantage.co/documentation/) is the best starting point for a prototype that needs one keyed REST API. It covers time series, fundamentals, economic data, and precomputed technical indicators. The documentation groups the API into nine categories: stock time series, indices, options, Alpha Intelligence, fundamentals, forex and crypto, commodities, economic indicators, and technical indicators. Stock time-series endpoints expose daily, weekly, monthly, and intraday resolutions. The documentation states 25+ years of historical depth for the stock time-series suite. Responses come back as JSON or CSV through a `datatype` parameter. Intraday freshness runs on a separate historical, delayed, or real-time entitlement from the base key. That breadth makes Alpha Vantage useful for testing a data model before you buy a specialist feed for the workload it settles on: python```python import requests url = "https://www.alphavantage.co/query" params = { "function": "TIME_SERIES_DAILY", "symbol": "IBM", "apikey": "demo", # Alpha Vantage's public demo key, scoped to the IBM symbol } response = requests.get(url, params=params) response.raise_for_status() data = response.json() daily = data["Time Series (Daily)"] latest_date = next(iter(daily)) latest_close = daily[latest_date]["4. close"] print(f"{latest_date}: close = {latest_close}") # Prints the latest trading date and close returned by the API. ``` `TIME_SERIES_DAILY` returns a dictionary keyed by date, with each entry holding open, high, low, close, and volume. The `demo` key above works against the `IBM` symbol without any signup, and most other symbols need a real key. A free key doesn't imply free real-time entitlements or commercial redistribution rights. Check the current plan table before you scale past the prototype stage. Financial Modeling Prep takes a different angle: instead of breadth across asset classes, it goes deep on statements and filings. ## 2. Financial Modeling Prep: Best Financial Data API for Statements and SEC Filings [Financial Modeling Prep](https://site.financialmodelingprep.com/developer/docs) fits financial statements and SEC filings, not a raw tick stream. Company profiles and screening fields round out the picture. The documentation exposes income statements, balance sheets, cash-flow statements, and SEC filings. The documentation also covers company profiles, CIK, CUSIP, and ISIN lookup, earnings data, analyst estimates, calendars, and bulk endpoints. Requests authenticate with an `apikey` value, passed as either a query parameter or a header, against a stable REST base URL. That inventory supports screeners, research systems, company-data enrichment, and filings workflows that need structured statement data rather than a price feed alone. Report dates and point-in-time behavior matter for backtests here. A current, restated statement isn't the statement a developer would have seen on the historical date it covers. A backtest built on today's numbers can look better than what a live system would have known at the time. Developers researching historical fundamentals commonly describe the opposite problem: broken or inconsistent records that need daily repair. That pain applies to fundamentals data broadly, not to Financial Modeling Prep specifically. FMP's own marketing language about accuracy and reliability isn't independent evidence, and not every dataset or bulk route ships on every plan. Confirm both against the current plan table before committing a workload. Massive takes the opposite emphasis again: live streams and bulk files over statement depth. ## 3. Massive: Best Financial Data API for Live Streams and Bulk Market Files Massive, formerly Polygon.io, is the best fit for an application that needs live WebSocket streams and on-demand REST queries. It also provides downloadable historical files from the same provider. The [Massive](https://massive.com/docs) documentation separates three access methods. REST covers historical and ad hoc queries, WebSocket covers continuous updates, and Flat Files cover bulk historical CSV data. The documented market families include stocks, options, futures, indices, forex, and crypto across all three access methods. The REST API adds economy and alternative data on top. That combination fits trading interfaces, market monitors, backtests, and machine-learning workloads that need both a live stream and batch history from the same source. "Real-time" still depends on the dataset and exchange entitlement you've purchased, the same caveat that applies to every provider on this list. Finnhub covers a narrower price surface but adds company-event data that sits outside Massive's focus. ## 4. Finnhub: Best Financial Data API for Company Events, News, and Estimates [Finnhub](https://finnhub.io/docs/api) is the best fit when an application needs price data alongside company news and events. Filings, estimates, and calendars round out the picture. The documentation covers quotes, WebSocket trades, company and market news, SEC filings, earnings calendars, recommendation trends, analyst estimates, fundamentals, economic data, and alternative datasets. REST requests authenticate through a `token` query parameter or an `X-Finnhub-Token` header, with both documented as equivalent. Official client libraries cover Python, Go, JavaScript, Ruby, Kotlin, and PHP. That combination fits a reader who wants to add news and events to a quote or company record. This approach skips stitching a separate calendar feed into the first prototype. The documentation restricts several endpoints to higher-tier plans, so dataset availability varies by plan instead of the full catalog shipping with a free key. Twelve Data solves a different problem: one time-series model across several asset classes instead of one asset class in depth. ## 5. Twelve Data: Best Financial Data API for Multi-Asset Time Series [Twelve Data](https://twelvedata.com/docs) is the best fit for one application that needs a common time-series surface. Stocks, forex, crypto, and ETFs all share the same model. The documentation lists time series, quotes, latest price, end-of-day price, cross listings, and exchange schedules. Fundamentals, technical indicators, and asset catalogs span over a million instruments. Delivery runs through REST, a WebSocket feed, and batch requests that pull several symbols in one call. Google Sheets and Excel add-ons cover spreadsheet workflows on the same data. That common symbol-discovery and time-series model saves a dashboard or research tool from rebuilding a separate integration per asset class. Coverage and real-time access differ by asset and exchange, so a single "global real-time" claim doesn't hold across the whole catalog. Verify the exact instrument before you build around it. EODHD takes multi-asset coverage further, with global history as the anchor instead of a shared time-series model. Scrapfly #### Scale your web scraping effortlessly Scrapfly handles proxies, browsers, and anti-bot bypass — so you can focus on data. [Try Free →](https://scrapfly.io/register)## 6. EODHD: Best Financial Data API for Global Historical Coverage [EODHD](https://eodhd.com/financial-apis/) is the best fit for a project that starts with global end-of-day history. It can later add intraday prices, fundamentals, corporate actions, and bulk downloads. The documented catalog includes end-of-day and intraday prices, live WebSocket data, tick data, split and dividend adjustments, screening, fundamentals, and SEC filings. Identifier mapping covers CUSIP, ISIN, FIGI, LEI, and CIK. Asset coverage spans stocks, ETFs, mutual funds, indices, forex, crypto, options, and economic data through separate endpoint families. That range fits global backtests, reference-data pipelines, corporate-action handling, and history-first research systems that expand into live data later. "Global" doesn't mean every exchange carries the same latency, history depth, or commercial rights. Validate the specific venue and license before you integrate it. Tiingo narrows the scope again, trading catalog breadth for explicit licensing language. ## 7. Tiingo: Best Financial Data API for Adjusted History and Explicit Usage Terms [Tiingo](https://www.tiingo.com/documentation/general/overview) is the best fit when adjusted historical data and corporate actions matter most. Clear usage boundaries matter more here than the broadest endpoint catalog. The documentation separates REST endpoints from a WebSocket feed built for continuous streaming. REST covers end-of-day history, news, crypto, forex, equity data, fundamentals, fund fees, dividends, and splits. REST responses come back as JSON or CSV. Tiingo publishes its own ticker symbology and a downloadable supported-ticker file. The permitted-use terms are unusually explicit. Lower-tier plans license data for internal and personal use only. A higher-tier account adds internal commercial use, and redistribution needs separate written approval naming the use case and company size. That clarity fits research and backtesting systems where licensing questions need answers before the product design locks in. Don't call the data cleaner or more accurate than the alternatives above without a shared benchmark. A commercial account alone doesn't grant redistribution rights. Alpaca closes the list with the one provider built around trading, not data delivery alone. ## 8. Alpaca: Best Financial Data API for Trading and Brokerage Integration The [Alpaca Market Data API](https://docs.alpaca.markets/us/docs/about-market-data-api) fits market data beside order execution or a brokerage product, not a standalone research database. The API provides historical and live equities, options, and crypto data over HTTP and WebSocket, with official SDKs for Python, Go, Node.js, and C#. Alpaca splits its product in two. The Trading API serves individual trading applications, and the Broker API serves partners building a brokerage product on top of Alpaca's platform. The current entry-level equities feed covers IEX rather than every US exchange, and only higher-priced tiers add full exchange coverage. That gap is the concrete reason you need to read "real-time" against its venue entitlement, on Alpaca and everywhere else on this list. Alpaca isn't the default pick for deep global fundamentals or broad cross-exchange reference data. Its strength sits in the trading-plus-data combination the other seven providers don't offer. Eight providers, eight different jobs. The next question is what to verify before any of them ships to production. ## What Must You Verify Before Choosing a Financial Data API? Verify the exact dataset, historical behavior, entitlement, and license before you integrate any of these providers. A successful test request proves connectivity, not product fit. Five failure modes account for most of the gap between a working prototype and a broken production system: - **Delayed data labeled real-time**: name the venue or feed and the actual delay before you design alerts or trading interfaces around it. - **Historical data rewritten later**: check split and dividend adjustments, and whether the underlying fundamentals are point-in-time or restated. - **Coverage without usable depth**: confirm the exact symbols, exchanges, history window, and fields your product needs. - **Access without redistribution rights**: confirm whether your license lets you display, cache, export, or serve the data back to your own users. - **Free prototype, paid production**: map the production request pattern and required datasets before you assume a free key scales to the deployed workload. A short test plan catches most of this before it reaches production: 1. Choose five representative symbols, including one edge case such as a delisted or multi-class security. 2. Fetch the same date range and fields from every provider on the shortlist. 3. Check timestamps, time zone, corporate actions, null handling, and rate-limit responses. 4. Read the license for the exact customer-facing use you have in mind. 5. Keep one known record as a regression fixture before you ever switch providers. | Criterion | What to check | What happens if you skip it | |---|---|---| | Coverage and freshness | Exact symbols, exchanges, and real-time versus delayed status | Alerts fire on a delay the UI labels as live | | History and adjustments | Split and dividend handling, point-in-time fundamentals | A backtest sees numbers it couldn't have known at the time | | Delivery | REST, WebSocket, or bulk files, and the rate limits on each | A live feature built on REST polling misses updates or gets throttled | | Entitlement | Which venues and asset classes the plan includes | Production requests 403 on symbols the free tier never covered | | Redistribution rights | Whether the data can reach your own end users | A shipped feature breaches the provider's license terms | Use this worksheet against your own shortlist before you write the first line of integration code, not after. [How to Turn Web Scrapers into Data APIsDelivering web scraped data can be a difficult problem - what if we could scrape data on demand? In this tutorial we'll be building a data API using FastAPI and Python for real time web scraping.](https://scrapfly.io/blog/posts/how-to-turn-web-scrapers-into-data-apis) Every check above assumes the provider has the data you need. The next section covers what to do when none of them do. ## When Should You Use Scrapfly Instead of a Financial Data API? Use a licensed financial data API when you need normalized feeds with a support contract behind them. Use Scrapfly when the data you need exists only on a public finance page or an undocumented web endpoint. You still need to retrieve that source reliably. | Data route | Best for | Contract | Main caveat | |---|---|---|---| | Financial data API | Normalized market feeds | Supported API | Dataset + license scope | | `yfinance` or hidden endpoint | Small source-specific jobs | Unofficial | Breakage + throttling | | Scrapfly Web Scraping API | Public finance pages | Managed fetch API | Source-specific terms and data rights | The Web Scraping API isn't an exchange feed, a market-data license, a brokerage API, or a substitute for redistribution rights. It gets you the page. What you're allowed to do with the extracted data is a separate question from any of the eight providers above. For Google's own historical finance data, see the [Google Finance API and alternatives](https://scrapfly.io/blog/posts/guide-to-google-finance-api). It covers `GOOGLEFINANCE` and scraping the live page. For Python access to unofficial Yahoo endpoints, see the [Yahoo Finance data in Python](https://scrapfly.io/blog/posts/guide-to-yahoo-finance-api). It covers `yfinance` and the Yahoo chart endpoint in depth. The second row of the table above uses a specific technique. [find a hidden API](https://scrapfly.io/blog/posts/how-to-scrape-hidden-apis) walks through locating an undocumented XHR endpoint a page's own frontend calls. ScrapFly's [Web Scraping API](https://scrapfly.io/products/web-scraping-api) is a single HTTP endpoint for collecting web data at scale. - [Anti-Scraping Protection bypass](https://scrapfly.io/docs/scrape-api/unblocker) - handles anti-bot challenges from Cloudflare, DataDome, HUMAN/PerimeterX, and Akamai. - [Smart proxy rotation](https://scrapfly.io/docs/scrape-api/proxy) - residential and datacenter pools with country and ASN level geo-targeting. - [JavaScript rendering](https://scrapfly.io/docs/scrape-api/javascript-rendering) - render SPAs and dynamic pages through real cloud browsers. - [Browser automation scenarios](https://scrapfly.io/docs/scrape-api/javascript-scenario) - scroll, click, fill forms, and wait for elements without managing a browser fleet. - [Format conversion](https://scrapfly.io/docs/scrape-api/getting-started#api_param_format) - return pages as HTML, JSON, clean text, or LLM ready Markdown. - [Session management](https://scrapfly.io/docs/scrape-api/session) - keep cookies, headers, and IPs consistent across multi step flows. - [Smart caching](https://scrapfly.io/docs/scrape-api/getting-started#api_param_cache) - cache successful responses to cut cost on repeat scraping jobs. - [Python](https://scrapfly.io/docs/sdk/python), [TypeScript](https://scrapfly.io/docs/sdk/typescript), [Scrapy](https://scrapfly.io/docs/sdk/scrapy), and [no-code integrations](https://scrapfly.io/docs/integration/getting-started) including [Make](https://scrapfly.io/integration/make), [n8n](https://scrapfly.io/integration/n8n), [Zapier](https://scrapfly.io/integration/zapier), [LangChain](https://scrapfly.io/integration/langchain), and [LlamaIndex](https://scrapfly.io/integration/llamaindex). ### Web Scraping API Scrape any website with our powerful API. Anti-bot bypass, JavaScript rendering, and rotating proxies built-in. [Try Web Scraping API](https://scrapfly.io/docs/scrape-api/getting-started) ## FAQ Is there a free financial data API for Python?Yes, several providers on this list offer free keys or entry plans, and `yfinance` gives no-key Python access to unofficial Yahoo endpoints. Free access doesn't prove real-time venue coverage, commercial rights, or production capacity on its own. Is yfinance an official Yahoo Finance API?No, `yfinance` is a community Python library that calls Yahoo's unofficial web endpoints. It's useful for small research jobs but has no supported API contract behind it. Can a financial data API return real-time and historical prices?Yes, several providers on this list expose both, but "real-time" and history depth are plan, asset, and venue specific. Verify exchange entitlement, delay, corporate-action adjustments, and the earliest available timestamp before you rely on either. Does Google Finance have an API in 2026?No, Google deprecated its original Finance API in 2011 and shut it down in 2012. Current routes are `GOOGLEFINANCE` in Sheets, a third-party financial data API, or scraping the public Google Finance page. What's the difference between a data API and web scraping for financial data?A financial data API delivers normalized fields under a documented license and support contract. Scraping retrieves a public page directly and extracts the fields it renders; source-specific terms and data rights still apply. Is scraping public finance pages legal?The legal position depends on the source, jurisdiction, data, and use case. Check the applicable terms and law before running a financial-data collection job at scale. ## Summary Choose the provider whose data job, access method, history, and rights match your product, then validate it against representative records before you commit. Start with Alpha Vantage, Finnhub, or Twelve Data when the immediate job is a prototype spanning common market data. Reach for Financial Modeling Prep, Massive, EODHD, Tiingo, or Alpaca for a more specific workload. That covers statements, live feeds, global history, adjusted research data, or trading integration. None of the eight cover a retailer, exchange, or field outside their own access model. Scrapfly's Web Scraping API is the route for public-page or hidden-endpoint data no licensed feed exposes. It's not a ninth entry in the comparison above. Legal Disclaimer and PrecautionsThis tutorial covers popular web scraping techniques for education. Interacting with public servers requires diligence and respect: - Do not scrape at rates that could damage the website. - Do not scrape data that's not available publicly. - Do not store PII of EU citizens protected by GDPR. - Do not repurpose *entire* public datasets which can be illegal in some countries. Scrapfly does not offer legal advice but these are good general rules to follow. For more you should consult a lawyer. [ Add as a preferred source ](https://google.com/preferences/source?q=scrapfly.io) Table of Contents Table of Contents- [Key Takeaways](#key-takeaways) - [Which Financial Data API Is Best for Developers in 2026?](#which-financial-data-api-is-best-for-developers-in-2026) - [How Were These Financial Data APIs Compared?](#how-were-these-financial-data-apis-compared) - [Project Setup](#project-setup) - [1. Alpha Vantage: Best Financial Data API for Prototypes and Technical Indicators](#1-alpha-vantage-best-financial-data-api-for-prototypes-and-technical-indicators) - [2. Financial Modeling Prep: Best Financial Data API for Statements and SEC Filings](#2-financial-modeling-prep-best-financial-data-api-for-statements-and-sec-filings) - [3. Massive: Best Financial Data API for Live Streams and Bulk Market Files](#3-massive-best-financial-data-api-for-live-streams-and-bulk-market-files) - [4. Finnhub: Best Financial Data API for Company Events, News, and Estimates](#4-finnhub-best-financial-data-api-for-company-events-news-and-estimates) - [5. Twelve Data: Best Financial Data API for Multi-Asset Time Series](#5-twelve-data-best-financial-data-api-for-multi-asset-time-series) - [6. EODHD: Best Financial Data API for Global Historical Coverage](#6-eodhd-best-financial-data-api-for-global-historical-coverage) - [7. Tiingo: Best Financial Data API for Adjusted History and Explicit Usage Terms](#7-tiingo-best-financial-data-api-for-adjusted-history-and-explicit-usage-terms) - [8. Alpaca: Best Financial Data API for Trading and Brokerage Integration](#8-alpaca-best-financial-data-api-for-trading-and-brokerage-integration) - [What Must You Verify Before Choosing a Financial Data API?](#what-must-you-verify-before-choosing-a-financial-data-api) - [When Should You Use Scrapfly Instead of a Financial Data API?](#when-should-you-use-scrapfly-instead-of-a-financial-data-api) - [FAQ](#faq) - [Summary](#summary) Join the Newsletter Get monthly web scraping insights Scale Your Web Scraping Anti-bot bypass, browser rendering, and rotating proxies, all in one API. Start with 1,000 free credits. No credit card required 1,000 free API credits Anti-bot bypass included [Start Free](https://scrapfly.io/register) [View Docs](https://scrapfly.io/docs/onboarding) Not ready? 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