Head-to-head · Data Marketplace Software
Monda Data Exchange Platform vs BigQuery sharing
Monda Data Exchange Platform leads on 0 checks, BigQuery sharing on 0, and 5 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreMonda Data Exchange Platform · 8.9/10
Monda Data Exchange Platform scores higher on our rubric for data marketplace software: 8.9 against 8.6 out of 10; our editors rank them #5 and #7.
On delivery methods, BigQuery sharing gives you Query where Monda Data Exchange Platform offers Api.
Monda Data Exchange Platform is the better fit for organizations needing private marketplaces. BigQuery sharing is the better fit for bigQuery-native data sharing.
- Monda Data Exchange Platform fits best
Organizations needing private marketplaces
- BigQuery sharing fits best
BigQuery-native data sharing
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Side by side
| Feature | Monda Data Exchange Platform 8.9/10 Visit ↗ | BigQuery sharing 8.6/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 8.9 | 8.6 |
| Ranking | #5 in Data Marketplace Software | #7 in Data Marketplace Software |
| Best for | Organizations needing private marketplaces | BigQuery-native data sharing |
| Pricing model | Paid | Paid |
| Starting price | — | Pricing on request |
| Free plan | — | Not checked yet |
| Free trial | — | — |
| Deployment | Cloud | Cloud |
| Platforms | Web | Web |
| Support | Email, Docs · 24/7 | Live chat, Phone, Tickets, Community, Docs |
| Compliance | ISO 27001, SSO/SAML | SOC 2, ISO 27001, HIPAA, PCI DSS |
| Integrations | 11 integrations | 3 integrations |
| Built for | Small business, Mid-market, Enterprise | Small business, Mid-market, Enterprise |
| Features Monda Data Exchange Platform 4/4 · BigQuery sharing 4/4 | ||
| Data transactions | ✓ | ✓ |
| Seller publishing | ✓ | ✓ |
| Access controls | ✓ | ✓ |
| Private marketplace | ✓ | ✓ |
| Specs | ||
| Delivery methods | Api | Query |
| Dataset listing limit | Not checked yet | Not checked yet |
| Commercial model | Custom | Custom |
| Our review | ||
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| Our verdict | Monda Data Exchange Platform is designed for data providers and organizations creating data-as-a-service offerings. It supports data-product creation, customization, publishing, selling, governance, and delivery across clouds and… Read the review → |
BigQuery sharing, formerly Analytics Hub, is a Google Cloud data exchange platform for publishing, discovering, subscribing to, and querying shared datasets and Pub/Sub topics. Providers can organize resources into public or private… Read the review → |
Strengths and trade-offs
Monda Data Exchange Platform — where it wins
- Supports private, white-label, and external marketplace publishing
- Provides entitlement controls, access groups, and row or column filters
- Connects marketplaces, clouds, warehouses, storage, APIs, and HubSpot
Where it doesn't
- Pricing is quote-based and requires contact with sales
- Standard supports up to 50 listings and 1,000 monthly syncs
- Professional supports up to 150 listings and 5,000 monthly syncs
BigQuery sharing — where it wins
- Shares datasets and Pub/Sub topics through public or private exchanges
- Enables read-only linked datasets without replicating underlying data
- Combines IAM controls, subscriptions, usage tracking, and Marketplace sales
Where it doesn't
- Pricing follows a contact-sales model rather than a published fixed plan
- Subscribers and publishers may incur underlying service-related charges
- Best suited to organizations already operating in the Google Cloud ecosystem
- Monda Data Exchange Platform8.9/10 · Pricing on request
A flexible platform for organizations building private, white-label, or cross-cloud data marketplaces.
Visit MondaFull verdict → - BigQuery sharing8.6/10 · Pricing on request
A BigQuery-native exchange for governed data sharing, discovery, and direct querying.
Visit Google CloudFull verdict →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update





