The 7 Best Real-Time Stock Data APIs for Investors and Developers in 2026 (In-Depth Analysis &…

The 7 Best Real-Time Stock Data APIs for Investors and Developers in 2026 (In-Depth Analysis & Comparison)

Many believe that to access high-quality financial data, you need to pay thousands of dollars for a Bloomberg terminal or settle for limited platforms like Yahoo Finance. The truth is different: today, there are powerful, affordable, and even free real-time stock data APIs you can integrate into your Python scripts, interactive dashboards, or algorithmic trading systems.

As W. Edwards Deming said:

In this article, I present a practical comparison of the 7 best financial APIs on the market (with a focus on real-time stock data). I include:

• Pros and cons of each API
• Pricing plans (free tiers and paid options)
• Key features and data coverage
• Recommendations by profile (analyst, trader, developer, or enterprise)
• Concrete use cases demonstrating each API
• Comparison table (quick selection guide)
• Frequently asked questions to address common doubts

Let’s dive in.

1. EODHD API (End-of-Day Historical Data)

Best for: Fundamental analysis, backtesting, and financial reports
Website: eodhd.com

Key features:

• Historical end-of-day (EOD) prices and intraday data (1m, 5m, 1h intervals)
• Fundamental data (financial ratios, balance sheets, income and cash flow statements)
• Corporate actions: dividends, stock splits, earnings, IPO data
• Macroeconomic indicators and earnings calendars
• Financial news API (with sentiment analysis)
• Broad coverage: stocks, ETFs, indices, forex, and cryptocurrencies

Highlights: EODHD provides clear documentation with plenty of Python examples, and it combines both quantitative price data and fundamental data in one service. This makes it great for building dashboards or predictive models that require both historical prices and financial metrics. Its data consistency (handling of splits, ticker changes, etc.) is also highly regarded.

Pricing:

• Free: 20 API requests per day (limited to basic end-of-day data) — useful for testing or small-scale scripts
• Pro: Plans from ~$17.99 per month (for individual market packages) up to ~$79.99 per month for an all-in-one global data package. The paid tiers offer generous limits (e.g. 100,000 API calls/day) and full access to historical and real-time data.

Cons:

• The free plan’s 20 calls/day is very limited, suitable only for trial runs or simple prototypes. Serious projects will need a paid plan.
• Some advanced features (like extensive options data or certain international markets) may require higher-tier subscriptions.

Use case: Extract Apple’s dividend history over the past 5 years and calculate the dividend yield trend. (EODHD’s API can provide historical dividend payouts which you can combine with price data for this calculation.)

Personal recommendation: If you need a single comprehensive API for global stocks (prices + fundamentals + news), EODHD is an excellent choice. ✨ Get 10% off here to try it out.

2. Alpha Vantage

Best for: Algorithmic trading, fintech apps, interactive dashboards & charting
Website: alphavantage.co

Key features:

• Time series data for equities (daily, intraday down to 1-minute)
• Technical indicators built-in (e.g. RSI, MACD, Bollinger Bands) — you can query indicator values directly via the API.
• Crypto and Forex data support
• Some sentiment and macroeconomic data (e.g. sector performance, economic indicators)

Highlights: Alpha Vantage is known for its ease of use and generous free tier for beginners. It’s one of the most popular starting points for developers learning to work with financial data. Uniquely, Alpha Vantage is an official vendor of Nasdaq market data, which speaks to its data reliability. The API responses are JSON by default, and the documentation includes examples that integrate well with Python and pandas.

Pricing:

• Free: Up to 5 API calls per minute (approximately 500 calls per day). This is sufficient for small applications or learning purposes, though heavy use will hit the limits quickly. (Note: Alpha Vantage’s standard free limit is actually 25 calls per day as of late 2024, enforced alongside the 5/minute rate.)
• Premium: Paid plans starting from $29.99/month for higher throughput (e.g. 30+ calls/minute) and no daily cap. Higher tiers (ranging up to ~$199/month) allow dozens or hundreds of calls per minute for enterprise needs.

Cons:

• Strict rate limits on the free tier. Hitting 5 calls/min means you often have to throttle your scripts or batch requests. For example, pulling intraday data for many symbols or calling many technical indicators will quickly require a paid plan.
• Limited depth in some areas: fundamental data coverage is basic (company overviews, a few ratios) and not as extensive globally as some competitors.

Use case: Build an email alert system that triggers when a stock’s 14-day RSI drops below 30 (an oversold signal). Alpha Vantage’s technical indicators API can directly return the RSI for a given symbol, making this straightforward to implement without calculating RSI manually.

3. Intrinio

Best for: Enterprise projects, advanced fundamental data, and large-scale financial applications
Website: intrinio.com

Key features:

• Extensive financial statement data: Intrinio provides detailed fundamentals — standardized and as-reported financials (income statements, balance sheets, cash flows) for thousands of companies. It’s very useful for deep fundamental analysis and modeling.
• Real-time and historical stock prices: Access to real-time equity quotes (for supported exchanges) and long historical price data (often decades back). Intrinio also offers options data, ETFs, Forex, and other asset classes through various packages.
• Data marketplace model: Intrinio has a variety of data feeds and endpoints (e.g., US stock prices, global equities, options, ESG data, etc.). You subscribe only to the feeds you need, which can be cost-efficient for specific use cases.
• Developer tools: Clean REST API with robust documentation, SDKs in multiple languages, and even a real-time data streaming option for certain feeds. They also provide a sandbox environment and live chat support to help during development.

Highlights: Intrinio is known for high data accuracy and quality. It’s the go-to for many fintech startups and even institutions when building platforms that require reliable and up-to-date financial data. The breadth of APIs and endpoints is massive — from stock screeners to data on insider transactions. Intrinio’s website and product pages are very informative, and they even include an AI chatbot to help you find the data you need.

Pricing:

• Free trial: Intrinio offers a free trial period for new users to test out the API with limited access. This is great for evaluating their data before committing.
• Paid packages: Pricing is segmented by data type. For example, a US equities core package starts around $200/month (Bronze tier) for end-of-day prices and fundamentals. Real-time stock price feeds and expanded data (Silver/Gold tiers) cost more — e.g., U.S. equities Gold (with real-time quotes and full history) is about $800/month. Similarly, options data packages range from ~$150 up to $1600/month for real-time options feeds. Intrinio’s model is pay for what you need, which scales up to enterprise-level contracts for wide coverage.

Cons:

• Not ideal for small projects or beginners: Intrinio’s offerings can be overkill for hobbyist use — the range of data is immense and the pricing is relatively high. There is no unlimited free tier, so after the trial you must budget for at least a few hundred dollars per month to continue using their data at any scale.
• Complex pricing structure: Because of the package system (separate feeds for stocks, options, etc.), it may be confusing to figure out exactly which plan(s) you need, and costs can add up if you require multiple data types. It’s geared more toward startups, fintech companies, or professionals with a clear data strategy (as opposed to one-size-fits-all simple pricing).
• Website account required: You’ll need to go through account setup and possibly consultation for certain datasets. It’s not as plug-and-play as some other services for quick experiments.

Use case: An investor relations platform could use Intrinio to automate financial report analysis — pulling in several years of standardized financials for dozens of companies to compare ratios and performance. Intrinio’s high-quality fundamentals and wide historical coverage make it ideal for such an application.

4. Polygon.io

Best for: Real-time market data (especially U.S. stocks) and high-frequency trading apps
Website:https://massive.com/

Key features:

• Real-time price feeds: Polygon provides live tick-by-tick price data for U.S. stocks, options, forex, and crypto. It supports streaming via WebSockets, so you can get quotes and trades in real time with low latency.
• Historical data down to ticks: You can access granular historical data, including full tick data and minute-by-minute bars for equities (often used for backtesting trading algorithms).
• WebSockets & Streaming: Excellent WebSocket API for streaming live quotes, trades, and aggregates. This is crucial for building live dashboards or trading bots that react to market movements instantly.
• Reference data & tools: Polygon also offers comprehensive reference data (company info, financials, splits/dividends, etc.) and endpoints like news, analyst ratings, and more. However, its core strength is market price data.

Highlights: Polygon.io stands out for performance and depth in the U.S. markets. If you need real-time stock prices or even need to stream every trade for a given stock, Polygon can handle it. Their documentation is well-structured and they have a developer-friendly interface with interactive docs. They also offer community resources and example code which make integration easier. Polygon’s pricing page clearly separates plans for different asset types, so you can pick what you need.

Pricing

• Free: The free tier allows 5 API requests per minute and limited historical data (e.g., 2 years of daily data). Real-time streaming might be restricted or delayed on the free plan (often 15-minute delayed data for stocks). This tier is good for trying out the API or basic apps that don’t require extensive data.
• Paid: Plans start at $29/month for higher call limits and more data access. For instance, Polygon’s “Starter” or “Developer” plans (around $29-$79/month) provide live data with certain limitations (like delayed vs real-time) and a cap on how far back you can fetch history. More advanced plans can go up to a few hundred per month for full real-time tick data and larger rate limits. (Polygon has recently rebranded some offerings under “Massive” but the pricing remains in this range for individual developers.)

Cons:

• Primarily U.S.-focused: Polygon’s strength is U.S. stocks and options. If you need comprehensive data for international markets, you’ll need other APIs. Its coverage outside the U.S. (for equities) is limited, so it’s not a one-stop solution for global portfolios.
• Costly for full real-time access: While entry plans are affordable, truly real-time professional data (especially if you need full tick data or entire market streaming) can become expensive. Higher-tier plans for real-time data (with no delay and high rate limits) can run into the hundreds per month, and certain data (like entire market breadth or entire options chains in real time) might require enterprise arrangements.
• Limited fundamentals/news: Polygon has some fundamental data and news, but it does not offer the depth in these areas that more fundamentally-oriented APIs (like EODHD or FMP) do. It focuses on pricing data.

Use case: Stream live quotes for AAPL and MSFT using Polygon’s WebSocket API and display a live updating chart in a web app. With just a few lines of code, you can subscribe to the ticker feed and get real-time price updates that drive an interactive chart (great for a day-trading dashboard or a demo of live market data).

5. Alpaca Markets

Best for: Building trading bots and executing live trades (with data included)
Website: alpaca.markets

Key features:

• Commission-free stock trading API: Alpaca is actually a brokerage platform that provides APIs, so you can place real buy/sell orders for U.S. stocks with zero commissions via their API. This sets it apart from pure data providers.
• Real-time and historical market data: Alpaca offers real-time price data (for stocks on the US exchanges) and historical data as part of its service. When you have a brokerage account, you get access to stock quotes and minute-level bars, etc., through the API.
• Paper trading environment: For developers, Alpaca’s paper trading is a big plus — you can simulate trading with virtual money. You get the same API for paper and live trading, which is ideal for testing your algorithmic strategies safely.
• Brokerage integration: You can manage orders, positions, and account info via API. This means you not only get data but can also automate an entire trading strategy (from data analysis to order execution) with Alpaca’s platform.

Highlights: Alpaca is a favorite for DIY algorithmic traders and hackathon projects because it lowers the barrier to entry for trading automation. With a few API calls, you can retrieve market data and send orders. It’s essentially an all-in-one trading service. The documentation is developer-centric, and there are official SDKs (Python, JS, etc.) as well as a vibrant community. Alpaca integrates with other tools (like TradingView, Zapier) and supports OAuth, making it easier to incorporate in different applications.

Pricing:

• Free tier: You can use Alpaca’s core API for free. Creating an account (which requires U.S. residency or certain other country residencies for live trading) gives you access to real-time stock data and the ability to trade with no monthly fee. Alpaca makes money if you trade (through other means like payment for order flow), so the API and basic data are provided at no cost to developers.
• Premium data plans: Alpaca does have optional subscriptions for more advanced data feeds. For example, the free data might be SIP consolidated feed with a small delay or only IEX data; if you need full real-time consolidated market data or extended history, they offer Data API subscriptions (like $9/month for more history, or higher for things like real-time news, etc.). These are add-ons; however, many users find the free data sufficient for starting out.

Cons:

• Limited to U.S. stock market: Alpaca’s trading and data are focused on U.S. equities. You won’t get direct access to international stocks or other asset classes (except crypto, which Alpaca has added in a separate offering).
• Requires KYC for live trading: If you plan to execute real trades, you must open a brokerage account with Alpaca, which involves identity verification and is only available in certain countries. Paper trading (demo mode) is available globally, but live trading has restrictions.
• Data not as extensive as dedicated providers: While Alpaca’s included data is decent, it may not be as comprehensive (in terms of history or variety of technical indicators) as some standalone data APIs. It’s primarily meant to support trading rather than be a full analytics dataset.

Use case: Create a Python trading bot that implements a simple moving average crossover strategy (e.g., buy when the 50-day MA crosses above the 200-day MA, sell on the reverse crossover). The bot can use Alpaca’s data API to fetch the latest prices for your stock, compute moving averages, and Alpaca’s trading API to place orders when signals occur. You can even run this in paper trading first to fine-tune the strategy.

6. Finnhub

Best for: A mix of data types (real-time prices, fundamentals, news, crypto) in one service
Website: finnhub.io

Key features:

• Real-time market data: Finnhub provides real-time quotes for stocks (free for US stocks via IEX), forex, and cryptocurrencies through its API. It’s a solid choice if you need live pricing across multiple asset classes.
• Financial news with sentiment: There’s a news API that returns the latest news articles for companies or markets, including sentiment analysis scores. This is useful for gauging market sentiment or doing news-driven strategies.
• Corporate and economic calendar data: Endpoints for earnings calendars, IPO schedules, analyst earnings estimates, and economic indicators are available. This variety helps investors and analysts stay on top of upcoming events.
• Fundamental data: Finnhub offers some fundamentals (e.g., company profiles, financial statements, key metrics), as well as alternative data like COVID-19 stats, and even ESG scores. However, some of these are limited in the free tier.

Highlights: Finnhub is like a Swiss Army knife — it covers a broad range of financial data in one API. Many startups use Finnhub to power their apps because it’s relatively easy to use and the free tier is generous in terms of number of calls. Developers also appreciate that Finnhub’s documentation is straightforward and they have examples for how to use each endpoint. It’s particularly notable for its news and social sentiment features, which not all finance APIs offer.

Pricing:

• Free: 60 API requests per minute are allowed on the free plan, which is quite high compared to most free plans. This includes real-time stock prices (US markets) and basic access to many endpoints. The free tier is for personal or non-commercial use and has some data limits (like certain endpoints or depth of history may be restricted).
• Pro: Paid plans start from $49–50 per month for individual markets or data bundles. Finnhub’s pricing can be a bit modular; for example, real-time international stock feeds or more historical data might each be priced separately (often ~$50/month per market). They also have higher plans (hundreds per month) for enterprise or for accessing all data with fewer limits. For many users, the $50/month range unlocks a lot of additional data useful for scaling up an application.

Cons:

• Limited free fundamentals: The free plan, while generous with call volume, does not include all data. For instance, certain fundamental data endpoints (like full financial statements or international market data) require a paid plan. This can be frustrating if you expect all features to work out of the box with the free API key. Essentially, you might hit “Access denied” for some endpoints until you upgrade.
• Pricing can add up: If you need multiple data types (say US stocks real-time, plus international stocks, plus in-depth fundamentals, etc.), Finnhub’s costs can increase quickly because each component may be an add-on. In comparison, some competitors’ bundled plans might be more cost-effective for broad needs.
• Website/UI is basic: Finnhub’s website isn’t the slickest and occasionally the docs have minor inconsistencies. This isn’t a huge issue, but it’s not as polished as some others like Alpha Vantage or Twelve Data in terms of user interface.

Use case: Pull the latest news headlines and sentiment for Tesla (TSLA) and display a “sentiment gauge”. With Finnhub’s news API, you can get recent news articles about Tesla along with a sentiment score (positive/negative). A developer could feed this into a simple app or dashboard to visualize how news sentiment is trending for the company.

7. Twelve Data

Best for: Quick visualizations, simple dashboards, and spreadsheet integrations
Website: twelvedata.com

Key features:

• Historical & real-time data for stocks, forex, crypto: Twelve Data covers many global markets, offering time series data at various intervals (intraday to daily) for equities, FX, and cryptocurrencies.
• Built-in visualization tools: Uniquely, Twelve Data provides a web UI where you can quickly generate charts and indicators from their data without writing code. It’s useful for non-developers or for quickly checking data visually.
• Easy integration with Python, Excel, etc.: They have a straightforward REST API and also provide connectors (like an Excel/Google Sheets add-in and integration guides for Python, Node, and other languages). This makes it appealing to analysts who might want data in Excel as well as developers.
• Technical indicators and studies: Twelve Data’s API can return technical indicators similar to Alpha Vantage. They also support complex queries like retrieving multiple symbols in one call, and even some fundamentals for certain stocks.

Highlights: Twelve Data markets itself as very user-friendly. For someone who is building a simple web app or learning to analyze stock data, Twelve Data’s combination of an intuitive API plus a pretty interface for quick tests is attractive. Another highlight is their freemium model with credits — this can be flexible if your usage is light. They also have educational content and a responsive support team. Many users praise the quality of documentation, which includes example requests and responses for every endpoint (so you can see what data you’ll get).

Pricing:

• Free (Basic): 8 API requests per minute (up to ~800/day). This free plan gives real-time data for US stocks, forex, and crypto, which is quite useful for small projects. However, certain features (like WebSocket streaming or extended history) are limited on the free tier.
• Paid plans: Grow plan from $29/month, Pro plan from $79/month, and higher tiers up to Enterprise. The pricing is based on a credit system: each API call “costs” a certain number of credits (e.g., 1 credit per quote, more credits for heavier endpoints). Higher plans give you more credits per minute and access to more markets. For example, the Pro plan (~$79) significantly raises rate limits (e.g. 50+ calls/min) and adds a lot more historical data and international market coverage. Enterprise ($1,999/mo) is for organizations needing very high limits and all data. The credit system is a bit complex to grasp at first, but effectively the more you pay, the more data and speed you get.

Cons:

• Free plan limitations: The Basic plan is fine for testing, but serious usage will bump into its limits (both in call volume and data depth). Also, some endpoints require higher plans, and real-time WebSocket access is mostly for paid users. In short, Basic is more of a trial.
• Credit-based pricing confusion: As noted, the concept of “API credits” and each endpoint having a weight can be confusing. For instance, an API call that fetches 100 data points might consume more credits than one that fetches 1 data point. New users may find it hard to estimate how many credits they need, compared to providers with simple call counts.
• Fewer specialty datasets: Twelve Data covers the essentials well, but it doesn’t have things like in-depth fundamentals or alternative data. Its focus is on price data and basic indicators. Large-scale applications needing extensive financial statement data or niche data (like options, sentiment) would need an additional source.

Use case: Build a lightweight crypto price dashboard that updates every 5 minutes. Using Twelve Data’s API, you could fetch the latest price for a set of cryptocurrencies (e.g., BTC, ETH) at a 5-min interval and display them in a Streamlit or Dash app. Twelve Data’s ease of integration means you could have this running quickly, and if you use their built-in visualization components, you might not need to code the charting yourself.

Quick Selection Guide by User Profile:

• If you’re an investor/analyst needing both fundamentals and price history: EODHD or FMP are excellent due to their rich fundamental datasets and broad market coverage
• If you’re a trader focused on real-time data and execution: Polygon.io (for raw real-time feeds) or Alpaca (for trading with built-in data) are tailored to your needs. Polygon for pure data speed; Alpaca if you also want to place trades via API.
• If you’re a developer or student learning the ropes, Alpha Vantage or Yahoo Finance via yfinance are very beginner-friendly. They have free access, simple endpoints, and plenty of examples to get you started in Python or JavaScript.
• If you need global market coverage in one service: EODHD, Finnhub, or FMP will give you international stocks, forex, crypto, and more under a single API — useful for broad applications or multi-asset platforms.
• If you prefer no-code or Excel integration: EODHD, FMP, and Twelve Data offer Excel/Google Sheets add-ons and straightforward no-code solutions, so you can fetch market data into spreadsheets or BI tools without programming.

Bonus: Financial Modeling Prep (FMP)

Best for: Advanced fundamental analysis and automated financial statement retrieval
Website: financialmodelingprep.com

Key features:

• Extensive financial statements coverage: FMP provides APIs for detailed financial statements (balance sheets, income statements, cash flows) for many public companies, including quarterly and annual data. They also offer calculated financial ratios and metrics, making it a favorite for equity analysts.
• Real-time and historical stock prices: You can get real-time quotes as well as historical daily and intraday price data for stocks. FMP covers stocks worldwide, plus ETFs, mutual funds, and cryptocurrencies.
• Specialty endpoints: There are unique APIs for things like DCF (Discounted Cash Flow) valuation, historical dividend and stock split data, insider trading information, and even ESG scores. This breadth is great for those building sophisticated models.
• News and alternative data: FMP includes a financial news feed, earnings calendar, and economic indicators. While not as deep on news sentiment as Finnhub, it’s a well-rounded data source for market context.

Highlights: FMP has gained a lot of traction as a developer-friendly alternative to more expensive data platforms. Its documentation is clear, with examples in multiple languages. One big plus is the Excel/Google Sheets integration — even non-coders can use FMP by installing their Google Sheets add-on and pulling data directly into a spreadsheet. The combination of fundamentals + market data in one API, along with affordable pricing, makes FMP very appealing for startups and students. In my personal experience, FMP’s fundamental data depth is excellent for building valuation models or screening stocks based on financial criteria.

Pricing:

• Free tier: FMP offers a free plan with a limited number of daily requests (e.g., 250 per day). The free tier gives access to basic endpoints — you can get some real-time quotes, key financial metrics, and historical data for a few symbols to test it out.
• Pro plans: Paid plans start at around $19.99/month, which is quite affordable. These plans increase the daily request limit substantially (into the thousands per day) and unlock more endpoints. Higher tiers (on the order of $50-$100/month) offer even larger call volumes and priority support. For most individual developers or small businesses, FMP’s paid plans provide a lot of data bang for the buck. Enterprise plans are also available if needed, but many will find the mid-tier plans sufficient.

Cons:

• Free plan restrictions: The free plan is mainly for trial or very light use — serious users will quickly find it inadequate (in terms of both request limits and available data). If you have an app in production, you’ll almost certainly need a paid plan, though fortunately the entry cost is low.
• Data normalization quirks: Because FMP aggregates data from various sources, you might notice slight inconsistencies or formatting differences across certain endpoints. For example, some lesser-used financial metrics might have different naming conventions or units. These are minor issues and FMP continually improves them, but it’s something to be aware of if you encounter an odd-looking field.
• Not focused on real-time streaming: FMP provides real-time quotes on paid plans, but it’s not a streaming service. If you need tick-by-tick streaming or ultra-low-latency data, a specialized API like Polygon or a broker feed would be necessary. FMP is more geared towards snapshots of data (which is fine for most analysis and moderate-frequency querying).

Why we include FMP: Lately, many developers (myself included) have been testing FMP for projects because of its rich fundamental dataset and solid documentation. It’s a strong alternative if you want advanced company metrics or need to automate financial statement analysis directly into your Python scripts or dashboards. For example, you could pull 10 years of financials for dozens of companies in seconds via FMP — something that’s invaluable for quantitative investing or academic research. FMP combines flexibility, affordability, and depth of data that few APIs offer in one package.

Frequently Asked Questions (FAQs)

❓ What’s the most complete API that combines fundamentals, historical prices, and news?
✅ If you need everything in one service, EODHD, FMP, and Alpha Vantage stand out. They each offer a balance of broad market coverage, reliable data, and depth. EODHD and FMP in particular have extensive fundamental and historical datasets (with news feeds) alongside real-time data, making them all-in-one solutions.

❓ Is there a free API with real-time stock data?
✅ Polygon.io provides limited real-time access on their free plan — you can get real-time quotes for U.S. stocks (with some delays or limits). Additionally, Finnhub’s free tier offers real-time data for U.S. markets (60 calls/min) which is quite generous. If you’re open to paid plans, FMP offers real-time quotes in its affordable paid tiers as well. And for an unofficial free route, Yahoo Finance data via the yfinance library can give near-real-time quotes (with no API key needed), though it’s not guaranteed or supported.

❓ I’m new to programming and want to learn using stock data. Which API is best?
✅ Alpha Vantage or Yahoo Finance (yfinance) are excellent for beginners. Alpha Vantage’s free tier and straightforward endpoints (plus a ton of community examples) make it easy to get started. The yfinance Python library lets you pull data from Yahoo Finance without dealing with complex API details – perfect for quick prototypes or learning pandas data analysis. Both integrate seamlessly with Python for learning purposes.

❓ Which API has the best global market coverage?
✅ EODHD, Finnhub, and FMP are known for their international coverage. EODHD covers dozens of exchanges worldwide (US, Europe, Asia, etc.) for both stock prices and fundamentals. Finnhub includes international stock data and forex/crypto. FMP also has a global equity coverage and even macro data for various countries. If you need data beyond just U.S. markets, these providers will serve you well.

❓ Can I use these APIs in Excel or Google Sheets without coding?
✅ Yes, several of them offer no-code solutions. EODHD, FMP, and Twelve Data all provide add-ins or integrations for Excel/Sheets. For example, EODHD and FMP have official Google Sheets functions after you install their add-on, letting you fetch stock prices or financial metrics into a spreadsheet cell. Twelve Data has an Excel plugin as well. This is ideal for analysts who prefer working in spreadsheets but still want live data updates.

Final Thoughts and Action Plan

You don’t need to be a big firm to access professional-grade financial data. Today’s landscape of financial APIs makes it possible for anyone — from a solo developer to a small startup — to get quality real-time stock data and more.

Follow these steps to get started:

1. Choose the API that best fits your profile and project needs. (Review the comparisons above to decide which one aligns with your requirements and budget.)
2. Sign up and get your free API key. Every platform listed offers a free tier or trial — take advantage of that to test the waters.
3. Connect the data to your tool of choice: whether it’s a Python script, an Excel sheet, or a custom dashboard, use the API documentation and examples to integrate live data into your workflow. Start with small experiments — e.g., pull one stock’s data and plot it.

By iterating on those steps, you’ll quickly gain familiarity with these APIs and unlock new possibilities, from automated trading bots to insightful financial dashboards.

Looking for a single API that does it all (fundamentals, historical prices, and news)? My recommendation is EODHD for its all-around strength in data coverage and value. It’s a one-stop shop for investors and developers alike.

Pro tip: You can try EODHD with a 10% discount using the link above, to kickstart your project with some savings. Happy data hunting, and may your analyses be ever insightful!

Sources: The information above is gathered from official documentation and user reviews of each platform, including their pricing pages and features as of 2025. For example, Alpha Vantage’s free call limits, Intrinio’s pricing tiers, and Twelve Data’s rate limits are based on published data. Always double-check the latest details on each provider’s website, as features and pricing can evolve over time.

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