GNews vs RavenPack (Bigdata.com): full comparison for 2026
Quick verdict
GNews (4.1/5) edges ahead of RavenPack (Bigdata.com) (3.9/5) overall. GNews is the better choice for indie developers needing affordable commercial news access. RavenPack (Bigdata.com) is the stronger option for quant funds and financial AI products. The right pick depends on your budget, how much history you need and whether you need full text.
GNews vs RavenPack (Bigdata.com): head-to-head summary
| Criterion | GNews | RavenPack (Bigdata.com) |
|---|---|---|
| Founded | Not disclosed | 2003 |
| HQ | Not publicly disclosed | Marbella, Spain |
| Team size | Not publicly disclosed | 201–500 |
| Rating | 4.1 / 5 | 3.9 / 5 |
| Primary differentiator | Two simple endpoints with commercial rights from €49.99 a month | Two decades of entity-level news sentiment built for trading signals |
| Pricing model | Monthly or yearly plans in euros | Enterprise subscription; per-token content licensing |
| Entry price | €49.99/mo | Custom quote |
| Formats & SDKs | REST API, JSON | REST API, JSON, Python SDK |
| Typical uses | News & content apps, AI & LLM apps, Marketing & PR | Financial services, Research & academia, AI & LLM apps |
GNews vs RavenPack (Bigdata.com): overview
GNews
GNews is a compact API with a search endpoint and a top-headlines endpoint, filtered by country, language and category. The site does not name its operator. It credits a studio called Gigathink and lists only a contact email, so company size and founding year are not public. Plans are priced in euros. The free tier allows 100 requests a day for non-commercial use with 30 days of history, Essential (€49.99 a month) adds commercial rights, 1,000 requests a day and articles back to 2020, and Business and Enterprise raise the daily quota to 5,000 and 25,000.
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.
Features: GNews vs RavenPack (Bigdata.com)
| Capability | GNews | RavenPack (Bigdata.com) |
|---|---|---|
| Full article text | ✓ | ✗ |
| Historical archive | ✓ | ✓ |
| NLP enrichment | ✗ | ✓ |
| Story/event clustering | ✗ | ✗ |
| Licensed publisher content | ✗ | ✓ |
| Streaming or webhooks | ✗ | ✗ |
| Free access | ✓ | ✗ |
Formats and SDKs: GNews vs RavenPack (Bigdata.com)
| Format / SDK | GNews | RavenPack (Bigdata.com) |
|---|---|---|
| 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: GNews vs RavenPack (Bigdata.com)
| Criterion | GNews | RavenPack (Bigdata.com) |
|---|---|---|
| Entry price | €49.99/mo | Custom quote |
| Pricing model | Monthly or yearly plans in euros | Enterprise subscription; per-token content licensing |
| Access models | Free tier, Monthly plans | Enterprise contract |
| Price transparency | Public price | Quote only |
| Price tier | Budget | Enterprise / quote |
Who each API suits: GNews vs RavenPack (Bigdata.com)
| Dimension | GNews | RavenPack (Bigdata.com) |
|---|---|---|
| Buyer type | Individuals to enterprise | Enterprise only |
| Typical uses | News & content apps, AI & LLM apps, Marketing & PR | Financial services, Research & academia, AI & LLM apps |
| Example use cases | A news widget or digest in a consumer app. A small SaaS feature that pulls headlines by country. | Backtesting news-driven trading strategies. Financial research assistants grounded in licensed news. |
| How you get access | Free tier | Enterprise contract |
GNews vs RavenPack (Bigdata.com): pros and cons
| GNews | |
|---|---|
| + | Two endpoints and plain parameters, so a working call takes minutes |
| + | Commercial rights start at €49.99 a month, and yearly billing cuts that by about 20% |
| + | Up to 100 articles per request on the top plan |
| + | Paid tiers include full article content |
| - | History only goes back to 2020 |
| - | The operator and its support capacity are opaque |
| - | No entity, sentiment or clustering data |
| 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 |
Who should choose GNews?
A typical fit: a news widget or digest in a consumer app.
Two simple endpoints with commercial rights from €49.99 a month. Paid access starts at €49.99/mo. Typical uses: News & content apps, AI & LLM apps, Marketing & PR.
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.
Decision matrix: GNews vs RavenPack (Bigdata.com)
| Your situation | Recommended choice |
|---|---|
| You want to start free before paying | GNews |
| Your budget is at the lower end | GNews |
| You need full article text in the response | GNews |
| You need years of historical news | Both |
| You need licensed premium or wire content | RavenPack (Bigdata.com) |
| You are wiring news into an LLM agent | RavenPack (Bigdata.com) |
Use case fit: GNews vs RavenPack (Bigdata.com)
| Use case | GNews fit | RavenPack (Bigdata.com) fit | Winner |
|---|---|---|---|
| News & content apps | Strong | Limited | GNews |
| AI & LLM apps | Strong | Strong | Both equally |
| Marketing & PR | Strong | Limited | GNews |
| Financial services | Limited | Strong | RavenPack (Bigdata.com) |
| Research & academia | Limited | Strong | RavenPack (Bigdata.com) |
Verdict: GNews vs RavenPack (Bigdata.com)
GNews (4.1/5) is the stronger overall choice as a news data source. Two simple endpoints with commercial rights from €49.99 a month.
RavenPack (Bigdata.com) (3.9/5) is worth a look if you need financial research assistants grounded in licensed news. If your situation matches that, RavenPack (Bigdata.com) is a competitive option.
Related comparisons
GNews vs RavenPack (Bigdata.com) FAQ
Is GNews better than RavenPack (Bigdata.com)?
GNews (4.1/5) scores higher overall, but "better" depends on your use case. GNews's strongest advantage: two endpoints and plain parameters, so a working call takes minutes. RavenPack (Bigdata.com)'s strongest advantage: point-in-time sentiment history suits backtesting.
How do GNews and RavenPack (Bigdata.com) differ in pricing?
GNews: monthly or yearly plans in euros, with paid access from €49.99/mo. RavenPack (Bigdata.com): enterprise subscription; per-token content licensing, priced by quote. Only GNews offers free access.
Which is better for enterprise: GNews or RavenPack (Bigdata.com)?
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 GNews and RavenPack (Bigdata.com)?
What sets GNews apart: two simple endpoints with commercial rights from €49.99 a month. What sets RavenPack (Bigdata.com) apart: two decades of entity-level news sentiment built for trading signals. They also differ on entry price (€49.99/mo vs Custom quote) and typical uses (News & content apps, AI & LLM apps vs Financial services, Research & academia).
Verify all details directly with each API before making a decision.