RavenPack (Bigdata.com) vs Marketaux: full comparison for 2026
Quick verdict
RavenPack (Bigdata.com) (3.9/5) edges ahead of Marketaux (3.7/5) overall. RavenPack (Bigdata.com) is the better choice for quant funds and financial AI products. Marketaux is the stronger option for fintech side projects needing ticker-tagged news cheaply. The right pick depends on your budget, how much history you need and whether you need full text.
RavenPack (Bigdata.com) vs Marketaux: head-to-head summary
| Criterion | RavenPack (Bigdata.com) | Marketaux |
|---|---|---|
| Founded | 2003 | Not disclosed |
| HQ | Marbella, Spain | Not publicly disclosed |
| Team size | 201–500 | Not publicly disclosed |
| Rating | 3.9 / 5 | 3.7 / 5 |
| Primary differentiator | Two decades of entity-level news sentiment built for trading signals | Per-entity sentiment scores on every article, even on the free plan |
| Pricing model | Enterprise subscription; per-token content licensing | Monthly request plans |
| Entry price | Custom quote | $29/mo |
| Formats & SDKs | REST API, JSON, Python SDK | REST API, JSON |
| Typical uses | Financial services, Research & academia, AI & LLM apps | Financial services, News & content apps |
RavenPack (Bigdata.com) vs Marketaux: overview
RavenPack (Bigdata.com)
RavenPack was founded in 2003, with Armando Gonzalez as co-founder and CEO. It is headquartered in Marbella, Spain, has a US entity in New York, and says in recent job postings that it employs more than 200 people. Its core product turns news from Dow Jones and tens of thousands of other sources into entity-level sentiment and event signals for hedge funds and banks, and academics can reach the same data through Wharton Research Data Services (WRDS). In 2024 it launched Bigdata.com, a research and retrieval platform with an API, and a later release added per-token licensing of premium content so agents pay for the excerpts they use. Pricing is not published.
Marketaux
Marketaux covers stock, crypto and forex news and tags each article with the tickers and entities it mentions, each scored for sentiment between -1 and 1. Listings put coverage at about 5,000 sources in 30+ languages and 200,000+ tracked entities (per company website; independently unverifiable). The free plan allows 100 requests a day at three articles per request, and the official pricing page lists Basic at $29 a month for 2,500 daily requests. Entity statistics and trending endpoints need a paid tier, and the site does not say who operates it or where.
Features: RavenPack (Bigdata.com) vs Marketaux
| Capability | RavenPack (Bigdata.com) | Marketaux |
|---|---|---|
| Full article text | ✗ | ✗ |
| Historical archive | ✓ | ✗ |
| NLP enrichment | ✓ | ✓ |
| Story/event clustering | ✗ | ✗ |
| Licensed publisher content | ✓ | ✗ |
| Streaming or webhooks | ✗ | ✗ |
| Free access | ✗ | ✓ |
Formats and SDKs: RavenPack (Bigdata.com) vs Marketaux
| Format / SDK | RavenPack (Bigdata.com) | Marketaux |
|---|---|---|
| REST API | ✓ | ✓ |
| Python SDK | ✓ | N/A |
| Node.js SDK | N/A | N/A |
| Webhooks | N/A | N/A |
| WebSocket | N/A | N/A |
| MCP server | ✓ | N/A |
| S3/bulk delivery | N/A | N/A |
| BigQuery | N/A | N/A |
Pricing comparison: RavenPack (Bigdata.com) vs Marketaux
| Criterion | RavenPack (Bigdata.com) | Marketaux |
|---|---|---|
| Entry price | Custom quote | $29/mo |
| Pricing model | Enterprise subscription; per-token content licensing | Monthly request plans |
| Access models | Enterprise contract | Free tier, Monthly plans |
| Price transparency | Quote only | Public price |
| Price tier | Enterprise / quote | Budget |
Who each API suits: RavenPack (Bigdata.com) vs Marketaux
| Dimension | RavenPack (Bigdata.com) | Marketaux |
|---|---|---|
| Buyer type | Enterprise only | Individuals to enterprise |
| Typical uses | Financial services, Research & academia, AI & LLM apps | Financial services, News & content apps |
| Example use cases | Backtesting news-driven trading strategies. Financial research assistants grounded in licensed news. | A stock news feed in a portfolio tracker. Sentiment features for a hobby trading model. |
| How you get access | Enterprise contract | Free tier |
RavenPack (Bigdata.com) vs Marketaux: pros and cons
| RavenPack (Bigdata.com) | |
|---|---|
| + | Point-in-time sentiment history suits backtesting |
| + | Researchers can access it through WRDS |
| + | Per-token licensing of premium content settles rights questions for AI agents |
| + | MCP and API access to the same licensed corpus |
| - | Priced and designed for financial institutions |
| - | Not suited to general news search in consumer apps |
| - | Bigdata.com pricing is not public |
| Marketaux | |
|---|---|
| + | Ticker and entity tagging saves building your own matcher |
| + | Sentiment is scored for each entity mentioned in an article |
| + | Commercial use from $29 a month |
| + | Crypto and forex as well as equities |
| - | The free plan returns only three articles per request |
| - | The operator is anonymous, which complicates vendor due diligence |
| - | Narrow focus on financial topics |
Who should choose RavenPack (Bigdata.com)?
A typical fit: backtesting news-driven trading strategies.
Two decades of entity-level news sentiment built for trading signals. Paid access is quote-based. Typical uses: Financial services, Research & academia, AI & LLM apps.
Who should choose Marketaux?
A typical fit: a stock news feed in a portfolio tracker.
Per-entity sentiment scores on every article, even on the free plan. Paid access starts at $29/mo. Typical uses: Financial services, News & content apps.
Decision matrix: RavenPack (Bigdata.com) vs Marketaux
| Your situation | Recommended choice |
|---|---|
| You want to start free before paying | Marketaux |
| Your budget is at the lower end | Marketaux |
| You need full article text in the response | Neither returns full text |
| You need years of historical news | RavenPack (Bigdata.com) |
| You need licensed premium or wire content | RavenPack (Bigdata.com) |
| You are wiring news into an LLM agent | RavenPack (Bigdata.com) |
Use case fit: RavenPack (Bigdata.com) vs Marketaux
| Use case | RavenPack (Bigdata.com) fit | Marketaux fit | Winner |
|---|---|---|---|
| Financial services | Strong | Strong | Both equally |
| Research & academia | Strong | Limited | RavenPack (Bigdata.com) |
| AI & LLM apps | Strong | Limited | RavenPack (Bigdata.com) |
| News & content apps | Limited | Strong | Marketaux |
Verdict: RavenPack (Bigdata.com) vs Marketaux
RavenPack (Bigdata.com) (3.9/5) is the stronger overall choice as a news data source. Two decades of entity-level news sentiment built for trading signals.
Marketaux (3.7/5) is worth a look if you need sentiment features for a hobby trading model. If your situation matches that, Marketaux is a competitive option.
Related comparisons
RavenPack (Bigdata.com) vs Marketaux FAQ
Is RavenPack (Bigdata.com) better than Marketaux?
RavenPack (Bigdata.com) (3.9/5) scores higher overall, but "better" depends on your use case. RavenPack (Bigdata.com)'s strongest advantage: point-in-time sentiment history suits backtesting. Marketaux's strongest advantage: ticker and entity tagging saves building your own matcher.
How do RavenPack (Bigdata.com) and Marketaux differ in pricing?
RavenPack (Bigdata.com): enterprise subscription; per-token content licensing, priced by quote. Marketaux: monthly request plans, with paid access from $29/mo. Only Marketaux offers free access.
Which is better for enterprise: RavenPack (Bigdata.com) or Marketaux?
RavenPack (Bigdata.com) sells enterprise contracts with negotiated volume and SLA terms. RavenPack (Bigdata.com) carries licensed publisher content, which matters for legal review.
What are the main differences between RavenPack (Bigdata.com) and Marketaux?
What sets RavenPack (Bigdata.com) apart: two decades of entity-level news sentiment built for trading signals. What sets Marketaux apart: per-entity sentiment scores on every article, even on the free plan. They also differ on entry price (Custom quote vs $29/mo) and typical uses (Financial services, Research & academia vs Financial services, News & content apps).
Verify all details directly with each API before making a decision.