Data Link Datasets
Nasdaq Data Link, originally founded as Quandl in 2011 and acquired by Nasdaq in 2018, is a cloud-based data marketplace that provides access to over 350 curated datasets via a single API.
Publisher review
Nasdaq Data Link, originally founded as Quandl in 2011 and acquired by Nasdaq in 2018, is a cloud-based data marketplace that provides access to over 350 curated datasets via a single API. It is designed for quantitative analysts, hedge fund professionals, retail investors, and data scientists who need ready-to-use numerical data—especially in finance—without the overhead of scraping, cleaning, and standardizing raw data. The platform serves more than 950,000 professionals, including analysts from top data-driven organizations worldwide.
The platform organizes data into three broad categories: core financial data (223 datasets covering equities, currencies, interest rates, options, indexes, mutual funds, real estate, energy, agriculture, metals, and futures), environmental, social, and governance (ESG) data, and alternative data from non-traditional sources. Users can access both free and premium datasets, with 72 free datasets and 238 paid ones under core financial data alone. The data is delivered via RESTful API, with official client libraries for Python (Quandl package), R, and Excel integration. Real-time and historical data are both available, and the platform includes extensive documentation and customer support.
Nasdaq Data Link competes directly with specialized data APIs such as OilPriceAPI (focused on energy pricing) and FXMacroData (focused on FX macro indicators). While Nasdaq Data Link offers unmatched breadth across asset classes and publishers—including proprietary Nasdaq indexes, Sharadar fundamentals, and the Nasdaq Fund Network covering about 45,000 investable products—FXMacroData provides a simpler, faster implementation path for FX-specific workflows with a flat $25/month subscription and second-level announcement timestamps. OilPriceAPI targets a narrower niche with straightforward energy price endpoints.
The honest trade-offs: pricing is a la carte and dataset-specific, so combining multiple premium feeds can lead to complex, escalating costs and integration overhead. Free access is limited compared to some competitors—only about 72 of 350+ datasets are free. Some premium datasets require separate subscriptions beyond the platform fee. Additionally, the platform's breadth means users must navigate a large catalog and understand publisher-specific licensing terms, which can slow discovery and procurement for those who only need a few focused indicators.
How it works
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350+ curated datasets
Provides access to over 350 trusted data sets covering core financial data, ESG data, and alternative data, with fewer than 1 in 100 analyzed datasets becoming products.
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RESTful API access
All datasets are available via a single API, with official client libraries for Python (Quandl package), R, and Excel integration for programmatic and spreadsheet workflows.
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Free and premium tiers
Offers 72 free datasets (e.g., economy, energy, agriculture) and 238 paid datasets across asset classes like equities, currencies, and options, with a la carte pricing.
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Real-time and historical data
Supports both real-time data feeds (e.g., Nasdaq Global Index Data Service) and historical time-series data, enabling backtesting and live trading strategies.
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Extensive documentation
Provides comprehensive API documentation, code examples, and customer support to help users integrate data into their applications quickly.
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Third-party publisher marketplace
Hosts datasets from third-party publishers such as Trading Economics, IQ Banker, and Sharadar, alongside proprietary Nasdaq and Quandl data.
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Multi-asset class coverage
Covers equities, currencies, interest rates, options, indexes, mutual funds, ETFs, real estate, venture capital, energy, agriculture, metals, and futures.
Strengths and trade-offs
Strengths
- Curated, high-quality data: fewer than 1 in 100 datasets analyzed become products, ensuring a vetted catalog.
- Wide range of data types: over 350 datasets spanning core financial, ESG, and alternative data across 14 asset classes.
- Integration with multiple tools: official APIs and libraries for Python, R, and Excel, plus support for RESTful calls.
- Flexible pricing with free access: 72 free datasets available, allowing users to test data before purchasing premium subscriptions.
Trade-offs
- Pricing is a la carte and dataset-specific, making total costs unpredictable when combining multiple premium feeds.
- Free access is limited compared to competitors like FXMacroData, which offers a flat $25/month subscription for all indicators.
- Some premium datasets require separate subscriptions beyond the platform fee, increasing integration complexity.
- The large catalog can be overwhelming for users who only need a few focused indicators, slowing discovery and procurement.
Pricing context
A la carte pricing for premium datasets; free access available for 72 datasets. No flat monthly subscription for all data; costs vary by dataset and publisher. FXMacroData charges $25/month for its full FX macro API, while OilPriceAPI offers tiered plans starting at a lower entry point.
Getting started with Data Link Datasets
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Sign up for an account
Go to the Nasdaq Data Link website and create a free account. Provide your email and set a password. After verifying your email, log in to access the dashboard and obtain your personal API key.
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Get your API key
In your account dashboard, locate the API key section. Copy your unique API key. This key authenticates all requests to the Nasdaq Data Link API and is required for data access.
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Install the Python client
Open your terminal and run 'pip install quandl' to install the official Python library. This library simplifies API calls and data retrieval for programmatic access to datasets.
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Load a free dataset
In a Python script, import quandl and set your API key with 'quandl.ApiConfig.api_key = "YOUR_KEY"'. Then use 'data = quandl.get("WIKI/AAPL")' to fetch Apple stock data from the free WIKI dataset.
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Schedule regular data updates
Write a Python script that calls the API for your chosen datasets and saves the data to a CSV file. Use a task scheduler like cron (Linux) or Task Scheduler (Windows) to run this script daily for automated updates.
Frequently Asked Questions
What is Nasdaq Data Link and what datasets does it offer?
Nasdaq Data Link is a cloud-based data marketplace offering over 350 curated datasets via a single API. It covers core financial data, ESG data, and alternative data across 14 asset classes including equities, currencies, interest rates, options, and commodities.
How much does Nasdaq Data Link cost and are there free datasets?
Nasdaq Data Link uses a la carte pricing for premium datasets, with costs varying by dataset and publisher. It offers 72 free datasets covering economy, energy, and agriculture, while 238 paid datasets require separate subscriptions. There is no flat monthly fee for all data.
How do I access Nasdaq Data Link data programmatically?
All datasets are accessible via a single RESTful API with official client libraries for Python (Quandl package), R, and Excel integration. The platform supports both real-time and historical data feeds, with comprehensive documentation and code examples to help users integrate quickly.
How does Nasdaq Data Link compare to FXMacroData and OilPriceAPI?
Nasdaq Data Link offers broader asset class coverage but with complex a la carte pricing. FXMacroData provides a simpler $25/month flat subscription for FX macro indicators with faster implementation. OilPriceAPI focuses narrowly on energy price endpoints with tiered plans starting lower.
What are the main strengths of using Nasdaq Data Link?
Key strengths include curated high-quality data with fewer than 1 in 100 datasets becoming products, over 350 datasets across 14 asset classes, integration with Python, R, and Excel, and 72 free datasets for testing before purchasing premium subscriptions.
What are the weaknesses or drawbacks of Nasdaq Data Link?
Weaknesses include unpredictable a la carte pricing when combining multiple premium feeds, limited free access compared to competitors like FXMacroData, separate subscriptions for some premium datasets, and a large catalog that can overwhelm users needing only a few focused indicators.
Alternatives
How Data Link Datasets compares
Direct head-to-head against 3 competitors. Picked by 7wData.
Data Link Datasets
- Pricing
- A la carte pricing for premium datasets; free access available for 72 datasets. No flat monthly subscription for all data; costs vary by dataset and publisher. FXMacroData charges $25/month for its full FX macro API, while OilPriceAPI offers tiered plans starting at a lower entry point.
- Target
- Nasdaq Data Link, originally founded as Quandl in 2011 and acquired by Nasdaq in 2018, is a cloud-based data marketplace that provides access to over
- Strength
- Curated, high-quality data: fewer than 1 in 100 datasets analyzed become products, ensuring a vetted catalog.
- Watch for
- Pricing is a la carte and dataset-specific, making total costs unpredictable when combining multiple premium feeds.
Crunchbase
- Pricing
- Custom/Contact sales
- Target
- Startups, investors, sales teams
- Deployment
- Cloud-based
- Strength
- Comprehensive company and funding data
- Watch for
- Limited free tier, enterprise pricing opaque
AlphaSense
- Pricing
- Custom/Contact sales
- Target
- Investment research, corporate strategy
- Deployment
- Cloud-based
- Strength
- AI-powered search across filings, transcripts, news
- Watch for
- Steep learning curve for advanced features
Morningstar Direct
- Pricing
- Custom/Contact sales
- Target
- Asset managers, wealth advisors
- Deployment
- Desktop/cloud hybrid
- Strength
- Deep historical fund and ETF analytics
- Watch for
- Legacy UI, slow for real-time data
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Sources
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