Data Link API
Nasdaq Data Link is a cloud-based API suite that provides access to a wide range of financial datasets, including core financial data, ESG data, and alternative data.
Publisher review
Nasdaq Data Link is a cloud-based API suite that provides access to a wide range of financial datasets, including core financial data, ESG data, and alternative data. Originally launched as Quandl in 2011 by quant Tameer Kalem—who envisioned a 'Wikipedia for numerical data'—the platform was acquired by Nasdaq in 2018 and rebranded as Nasdaq Data Link in September 2021. It is designed for quantitative analysts, data scientists, and financial professionals who need ready-to-use, standardized data without the overhead of scraping, cleaning, and normalizing raw information. The platform serves users ranging from individual traders to institutional investors, offering both free and premium datasets across equities, currencies, fixed income, options, indexes, mutual funds, ETFs, real estate, venture capital, energy, agriculture, metals, futures, and economic indicators. With 72 free datasets and 238 paid datasets as of the latest count, it aims to solve the 'needle in a haystack' problem of extracting actionable insights from the growing volume of financial data.
Accessing data via Nasdaq Data Link is done through a suite of streaming and REST APIs that support real-time, delayed, and historical data delivery. The APIs are designed for flexible integration with existing systems, supporting multiple programming languages including Python, R, Excel, and SQL. Users can select specific endpoints for market coverage, asset classes, timestamps, and display requirements. The platform includes comprehensive documentation and tools for data analysis, and the Quandl Python package (e.g., `pip install quandl`) allows direct API calls using a free API key. The data is categorized by publisher—Nasdaq, Quandl, and third parties like Trading Economics and IQ Banker—and by data type (prices & volumes, fundamentals, estimates, etc.). The platform is highly scalable, capable of supporting real-time exchange data delivery with low latency, and Nasdaq operates four North American equity markets, including the Nasdaq Stock Market, the largest liquidity pool by market share.
In the market for financial data APIs, Nasdaq Data Link competes with providers like OilPriceAPI and FXMacroData. OilPriceAPI focuses specifically on oil and energy price data, while FXMacroData offers macroeconomic and FX data with a simpler pricing model. Nasdaq Data Link differentiates itself through its extensive breadth—covering 16 asset classes and over 300 datasets—and its integration with Nasdaq's own exchange data, index data (with over $900 billion in AUM as of 2025), and alternative data products. However, its complexity and dataset-specific pricing can be a barrier compared to more focused competitors. The platform's acquisition by Nasdaq in 2018 gave it access to Nasdaq's market infrastructure and client base, but also tied its pricing and access policies to a large corporate structure.
The honest trade-offs of Nasdaq Data Link are significant. First, pricing is dataset-specific, making it difficult to forecast total spend; users may need separate subscriptions for each premium dataset, and costs can escalate quickly—Reddit users report spending $2,000–$3,000 just for the data feed, plus $500–$6,500 in display fees, with additional per-display fees around $1. Second, the platform lacks a unified subscription model, so managing multiple data subscriptions becomes administratively complex. Third, while the free tier offers 72 datasets, many valuable datasets (e.g., real-time exchange data, alternative data) require paid subscriptions, limiting access for hobbyists or small firms. Fourth, the platform's reliance on the legacy Quandl API means that some newer features (e.g., streaming APIs) may have a steeper learning curve for users accustomed to modern RESTful designs. Finally, the breadth of data can be overwhelming; users must invest time in navigating the catalog and understanding which datasets are relevant to their use case.
How it works
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Core financial data
Provides 223 datasets across equities, currencies, fixed income, options, indexes, and more, with 72 free and 238 paid datasets.
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ESG data
Offers environmental, social, and governance datasets for sustainable investing analysis.
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Alternative data
Covers non-traditional datasets like satellite imagery, web traffic, and consumer behavior for alpha generation.
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Real-time & delayed APIs
Streaming and REST APIs deliver real-time, delayed, or historical data with selectable endpoints for market coverage.
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Multi-language support
Supports Python, R, Excel, and SQL, with a Quandl Python package for direct API calls using a free key.
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Comprehensive documentation
Includes detailed API docs, data catalogs, and analysis tools to help users integrate and interpret data.
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Scalable cloud delivery
Highly scalable infrastructure supports real-time exchange data delivery with low latency for enterprise applications.
Strengths and trade-offs
Strengths
- Extensive coverage across 16 asset classes and over 300 datasets, including core financial, ESG, and alternative data.
- Highly scalable and robust real-time exchange data delivery, leveraging Nasdaq's own market infrastructure.
- Flexible integration with existing systems via REST and streaming APIs, supporting Python, R, Excel, and SQL.
- Offers 72 free datasets, providing a low-cost entry point for users to evaluate the platform before committing to paid subscriptions.
Trade-offs
- Pricing is dataset-specific, making it difficult to forecast total spend; users may need separate subscriptions for each premium dataset.
- Requires separate subscriptions for premium datasets, leading to potential complexity in cost management and administrative overhead.
- Display fees can be high, with Reddit users reporting $500–$6,500 in display fees plus ~$1 per display, on top of $2,000–$3,000 for the feed.
- The breadth of data can be overwhelming, requiring significant time investment to navigate the catalog and identify relevant datasets.
Pricing context
Free tier includes 72 datasets; premium datasets require separate subscriptions with costs varying by dataset. Reddit users report $2,000–$3,000 for the feed, $500–$6,500 in display fees, and ~$1 per display fee.
Getting started with Data Link API
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Sign up for an API key
Go to the Nasdaq Data Link website and create a free account. After registration, you will receive a free API key. This key is required to authenticate all API requests and access both free and paid datasets.
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Install the Quandl Python package
Open your terminal and run `pip install quandl` to install the Quandl Python package. This library simplifies making API calls to Nasdaq Data Link and supports data retrieval in pandas DataFrames.
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Set your API key in code
In your Python script, import the quandl module and set your API key using `quandl.ApiConfig.api_key = 'YOUR_API_KEY'`. Replace 'YOUR_API_KEY' with the key from your account to authenticate requests.
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Download a free dataset
Use the `quandl.get('WIKI/AAPL')` function to retrieve historical stock data for Apple from the free WIKI dataset. This returns a pandas DataFrame with columns like Open, High, Low, Close, and Volume.
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Schedule regular data updates
Write a Python script that runs daily using a task scheduler (e.g., cron on Linux or Task Scheduler on Windows). The script should call the API for your datasets and save the data to a local database or CSV file for analysis.
Frequently Asked Questions
What is Nasdaq Data Link?
Nasdaq Data Link is a cloud-based API suite providing access to financial datasets like core financial, ESG, and alternative data. Originally launched as Quandl in 2011, it was acquired by Nasdaq in 2018 and rebranded in 2021 for quantitative analysts and financial professionals.
How do I access data through Nasdaq Data Link?
You access data via streaming and REST APIs supporting real-time, delayed, or historical delivery. The APIs integrate with Python, R, Excel, and SQL. Use the Quandl Python package with a free API key for direct calls, with comprehensive documentation available.
What types of financial data does Nasdaq Data Link offer?
It offers core financial data across 16 asset classes, ESG data for sustainable investing, and alternative data like satellite imagery. With 72 free and 238 paid datasets, it covers equities, currencies, fixed income, options, indexes, and more.
How much does Nasdaq Data Link cost?
Pricing is dataset-specific with no unified subscription. The free tier includes 72 datasets. Premium datasets require separate subscriptions, with Reddit users reporting $2,000–$3,000 for the feed plus $500–$6,500 in display fees and about $1 per additional display.
What are the main drawbacks of Nasdaq Data Link?
Key drawbacks include dataset-specific pricing making cost forecasting hard, separate subscriptions for each premium dataset, high display fees, and an overwhelming breadth of data. The legacy Quandl API also has a steeper learning curve for modern RESTful users.
How does Nasdaq Data Link compare to other financial data APIs?
Nasdaq Data Link offers broader coverage across 16 asset classes and over 300 datasets, including Nasdaq exchange data. Competitors like OilPriceAPI focus on oil prices, while FXMacroData offers simpler pricing. However, its complexity and dataset-specific costs can be barriers.
Alternatives
- OilPriceAPI ↗
- Netrows ↗
- Proxycurl ↗
How Data Link API compares
Direct head-to-head against 3 competitors. Picked by 7wData.
Data Link API
- Pricing
- Free tier includes 72 datasets; premium datasets require separate subscriptions with costs varying by dataset. Reddit users report $2,000–$3,000 for the feed, $500–$6,500 in display fees, and ~$1 per display fee.
- Target
- Nasdaq Data Link is a cloud-based API suite that provides access to a wide range of financial datasets, including core financial data, ESG data, and
- Strength
- Extensive coverage across 16 asset classes and over 300 datasets, including core financial, ESG, and alternative data.
- Watch for
- Pricing is dataset-specific, making it difficult to forecast total spend; users may need separate subscriptions for each premium dataset.
OilPriceAPI
- Pricing
- $15-$129/month with free tier
- Target
- Developers, trading bots, energy apps
- Deployment
- REST API
- Strength
- 100+ commodities, sub-second latency
- Watch for
- Free tier limited to 7-day trial
Netrows
- Pricing
- €49/month (10,000 credits)
- Target
- Developers needing LinkedIn + X data
- Deployment
- REST API
- Strength
- 48+ LinkedIn endpoints, real-time data
- Watch for
- Newer platform, no SDKs yet
Proxycurl
- Pricing
- $49/month (100 credits)
- Target
- Developers focused on LinkedIn data
- Deployment
- REST API
- Strength
- Established provider, Python SDK
- Watch for
- Expensive per credit, limited endpoints
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