Selling a data product on a marketplace is not a SaaS listing pointed at data buyers. The buyer never runs your software; they subscribe to a dataset and query it. That one difference changes how the product is delivered, how the buyer is entitled to it, and how you are allowed to price it — and it works differently again on AWS Data Exchange than on Snowflake.
A team that already ships a SaaS product on AWS Marketplace usually approaches its first data listing as a variation on a theme. They know the motion — build a listing, a buyer subscribes, the buyer provisions the software — and they assume a dataset is the same thing with a different payload.
It is not. When you sell software, the transaction ends with the buyer running something in their account. When you sell data, the transaction ends with the buyer querying something — a dataset they subscribe to, not a binary they deploy. Nothing is provisioned. That single shift moves three things a SaaS listing never made you think about: how the data is delivered, how a subscriber is entitled to it, and which pricing shapes the marketplace even allows.
This is a MOFU decision, not a first-touch one — you have a data product and you are choosing the listing type. Here is how a data listing actually differs from a SaaS one, on the two marketplaces where the distinction is sharpest: AWS Data Exchange and Snowflake.
What is a data product on a marketplace?
A data product on a marketplace is a listing whose unit of value is a dataset or data feed a buyer subscribes to and queries, rather than software the buyer deploys and runs. On AWS the listing type is AWS Data Exchange; on Snowflake it is a data listing built on Secure Data Sharing. Both sit next to the software listings in the same marketplace, and both transact through the same billing and disbursement plumbing — but what changes hands is access to data, not a running application.
That framing decides everything downstream. A SaaS listing asks “how does the buyer stand this up in their environment.” A data listing asks “how does the buyer get entitled to query this, and where does the data physically sit while they do.” The answer is not one answer — it splits by delivery mechanism, which is the first thing to get right.
Three product shapes fit the data-listing model:
- Static or slowly-changing datasets — a corpus a buyer subscribes to once and queries: reference data, historical prices, firmographics, a labeled training set.
- Dynamic data feeds — a dataset you revise on a cadence, where the buyer wants the current version without re-subscribing each time.
- Query-time data access — direct read access to data that stays under your control and updates continuously, so the subscriber always sees the latest state.
If your product only makes sense as an application a customer operates, it is a SaaS or container listing, not a data one. If it makes sense as data a customer joins against their own tables, a data listing is the right shape — and the delivery mechanics below are where the SaaS instinct stops helping.
How does data-product delivery differ from a SaaS listing?
Delivery is the mechanic with no SaaS equivalent: a SaaS listing hands the buyer software to run, while a data listing hands the buyer entitled access to data through one of several delivery modes, and each mode determines whether the data is copied or queried in place. On a SaaS listing the buyer operates their own instance; on a data listing you choose, per data set, whether the subscriber gets a copy or read access to data you still hold.
On AWS Data Exchange, the delivery mode is a property of the data set inside the product, and the documentation is explicit that the choice changes what the subscriber receives:
- Files (Amazon S3 objects) — AWS Data Exchange “creates a copy of the data set,” which the subscriber accesses as an entitled data set. The buyer gets a snapshot.
- Amazon S3 data access — the subscriber gets “the same Amazon S3 objects that the data provider maintains,” which “provides the most current data available.” You share direct access; nothing is copied.
- Amazon API Gateway APIs — requests “proxy through to your Amazon API Gateway API,” so the subscriber calls your live API through the AWS Data Exchange endpoint.
- Amazon Redshift data sets — the subscriber gets “read-only access to the tables, views, schemas, and user-defined functions” in your datashare.
- AWS Lake Formation (Preview) — read-only access to data associated with the LF-tags in the data set, queryable through services like Amazon Athena and Redshift Spectrum.
Snowflake collapses this to a single, stronger rule: a listing “is an enhanced method of Secure Data Sharing.” The consumer queries the data in place, inside their own Snowflake account, and nothing is ever copied or moved. There is no “copy” delivery mode to choose — the whole channel is query-in-place by design.
The practical consequence: the packaging work for a data listing is choosing and wiring a delivery mode, not building a deployable artifact. That is engineering a SaaS listing never asked of you, and it is the part a “port our listing” plan silently skips.
How does entitlement work for a data product?
Entitlement is the second mechanic that diverges: a SaaS listing entitles the buyer to run the software, while a data listing entitles the buyer to read a specific dataset, and the marketplace enforces that grant rather than a license key in your app. You do not ship an entitlement check to enforce yourself — the marketplace grants and revokes the subscriber’s access to the data set directly.
On AWS Data Exchange, a subscription is the entitlement: once a buyer subscribes, the data set becomes an entitled data set they can access under the delivery mode you chose, and the entitlement ends when the subscription does. Two provider controls sit on top of it. Subscription verification lets you require that “subscribers must request a subscription to your product,” giving you a chance to review who they are before they get access — the gate for regulated or restricted data. And you keep contractual control through the Data Subscription Agreement (DSA), the terms every subscriber agrees to before purchase, where you set use, warranty and governing-law clauses.
On Snowflake, the entitlement is the share itself: subscribing grants the consumer access to query your data through the listing, in their own account, and revoking the listing withdraws it. Neither marketplace asks you to build the enforcement — that is the point. A SaaS listing leaves entitlement partly in your code; a data listing puts it entirely in the marketplace’s grant, which is less code for you and a different mental model for your team.
How is data-product pricing different?
Pricing is the third divergence, and the one most likely to trip a SaaS team: the pricing shapes a data listing supports are built around a subscription to data, not a right to run software, so the familiar SaaS meters do not all carry over. A data listing prices duration-based access or metered querying of the dataset — not seats, not instance-hours, not per-deployment.
On AWS Data Exchange, an offer defines “the total price and duration of the subscription.” Durations run 1–36 months, and a public offer can present up to five duration/price combinations in a single offer; the subscriber “must choose a single price and duration when they subscribe” and pay upfront. You control auto-renewal (set once, at offer creation) and the refund policy. For individually negotiated deals, custom offers — including private offers and Bring Your Own Subscription (BYOS) — set specific terms and pricing for a selected AWS account, the data-listing analogue of a private offer on the software side.
On Snowflake, a paid data listing prices two ways: usage-based, billed in arrears in months where usage occurs (down to a fixed price per query that accesses paid data), or subscription, charging for a specified term. Payout then follows one of two paths — Stripe pays you for card purchases, and Snowflake pays you when the consumer draws down their Capacity commitment. The committed-spend path is the strategically interesting one: a buyer can spend budget they have already committed to Snowflake on your data, the same committed-spend dynamic that makes the hyperscaler marketplaces work.
The trap for a SaaS team is reaching for a per-seat or per-instance meter that a data listing has no place for. Price the subscription or the query, not the deployment that never happens.
Comparison table: data-product listing on AWS Data Exchange vs Snowflake vs a SaaS listing
The single most useful thing to hold in your head is that “put our data on a marketplace” resolves to a listing type with its own delivery, entitlement and pricing — and that those differ again between AWS Data Exchange and Snowflake. Here is how the two data paths line up against the SaaS listing you already know.
| AWS Data Exchange | Snowflake data listing | SaaS listing (for contrast) | |
|---|---|---|---|
| What you distribute | A dataset, data feed, or data-access product | Shared access to data in the consumer’s Snowflake account | Software the buyer deploys or provisions |
| Delivery | Per data set: S3 copy, S3 data access, API Gateway proxy, Redshift datashare, or Lake Formation | Secure Data Sharing — queried in place, never copied | Buyer stands up and runs their own instance |
| Is data copied? | Depends on the mode — S3 objects copy; data access and datashare do not | No — query-in-place by design | N/A (buyer runs the software) |
| Entitlement | Subscription = entitled data set; optional subscription verification; DSA terms | Subscription grants query access to the share | License enforced partly in your application |
| Pricing shapes | Subscription by duration (1–36 months, up to 5 per public offer, paid upfront) | Usage-based (per query / monthly) or subscription | Subscription, usage/metered, contract |
| Negotiated deals | Custom offers — private and BYOS | Private paid listing to specific consumers | Private offer |
| Committed-spend payment | Buyer’s AWS committed spend, via AWS Marketplace | Snowflake Capacity commitment drawdown | Cloud committed spend drawdown |
The takeaway is not that one path is better; it is that your data product fits a data listing cleanly and a SaaS listing badly, and that the two data marketplaces make different promises about whether the data ever leaves your control. A dataset a buyer wants a static copy of is an S3-objects product on AWS Data Exchange; a dataset a buyer should always see the latest of is S3 data access or a Snowflake share. Forcing a data product into the SaaS shape you already have is where a first data listing stalls. For the fuller picture of the Snowflake side specifically, Snowflake Marketplace for data and AI products walks through its provider and transaction model end to end.
Frequently asked questions
What is a data product on a marketplace? A data product is a marketplace listing whose unit of value is a dataset a buyer subscribes to and queries, not software the buyer deploys. On AWS it is an AWS Data Exchange listing; on Snowflake it is a data listing built on Secure Data Sharing.
How is an AWS Data Exchange listing different from a SaaS listing? A SaaS listing hands the buyer software to run. An AWS Data Exchange listing entitles the buyer to a dataset through a delivery mode you pick — an S3 copy, S3 data access, an API Gateway proxy, or a datashare. The buyer queries the data; nothing is provisioned.
How does delivery work for a data product on AWS Data Exchange? Per data set. Files (S3 objects) are copied to the subscriber. S3 data access, API Gateway, Redshift datashare and Lake Formation give read access to data you still maintain, so the subscriber sees the current version. You choose the mode when you build the product.
How do you price a data product on a marketplace? By subscription to the data, not by seats or instances. AWS Data Exchange offers price a subscription over a duration of 1–36 months, paid upfront, with up to five duration options per public offer. Snowflake prices usage-based (per query or monthly) or by subscription.
How does entitlement work for a data product? The marketplace grants it — you do not enforce a license key in your app. On AWS Data Exchange a subscription turns the data set into an entitled data set, with optional subscription verification. On Snowflake the subscription grants query access to the share.
Can data products use private, negotiated pricing? Yes. AWS Data Exchange supports custom offers — private and Bring Your Own Subscription (BYOS) — that set specific terms and pricing for a selected AWS account. Snowflake supports private paid listings offered to specific consumers. Both are the data-listing analogue of a private offer on the software side.
Takeaways
- A data product is a listing a buyer subscribes to and queries, not software they deploy. The three things a SaaS listing never made you think about — delivery, entitlement, pricing — are exactly the three that differ, so scope it as new packaging work, not a port.
- Delivery is the mechanic with no SaaS equivalent. On AWS Data Exchange you pick a delivery mode per data set — an S3 copy, S3 data access, an API Gateway proxy, a Redshift datashare, or Lake Formation — and it decides whether the buyer gets a snapshot or the current data. Snowflake is query-in-place only; nothing is copied.
- Entitlement is granted by the marketplace, not enforced in your app. A subscription becomes an entitled data set on AWS Data Exchange (with optional subscription verification and a DSA you control) or query access to a share on Snowflake.
- Pricing is subscription-to-data, not per-seat or per-instance. AWS Data Exchange prices duration-based subscriptions (1–36 months, paid upfront); Snowflake prices usage-based or subscription. Both support private and negotiated offers.
- Choose the marketplace by where the buyer keeps their data and committed spend, and run every listing — data and software — off one catalogue and one reconciliation surface, so the data listing does not become its own project.
Suger transacts on six marketplaces — AWS, Microsoft, Google Cloud, Snowflake, Alibaba Cloud, and Oracle — so a data listing runs through the same catalogue, offers and metering as your software ones instead of a separate console. See how the same listing and offer model works across every marketplace on product listing and offer management, start with the AWS Marketplace solution, or read the provider-side mechanics at Snowflake Marketplace documentation.
Sources
Primary sources for the platform rules cited above. Last verified August 20, 2026. Cloud providers change fees, eligibility, and program terms without notice — check the source before relying on a figure.
- Providing AWS Data Exchange data products on AWS Marketplace — The provider flow, the five data-set delivery types (S3 objects copy, S3 data access, API Gateway proxy, Redshift datashare, Lake Formation), subscription verification, custom/private/BYOS offers, and provider financials/disbursement.
- Creating an offer for AWS Data Exchange products — Offer pricing as 1–36 month durations (up to 5 per public offer, paid upfront), the Data Subscription Agreement, auto-renewal, and public/private/BYOS offer types.
- Snowflake Documentation: About listings — Defines a listing as an enhanced method of Secure Data Sharing — the consumer queries the data in place, in their own account, with no copy.
- Snowflake Documentation: Paid listings pricing models — The usage-based and subscription pricing models for a paid data listing, and the Stripe-versus-Capacity-commitment payout paths.
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