How do you choose your [ data marketplace ] solution?
Not all data marketplaces are created equal. Your technology choice will shape your organization for the next 3 to 5 years. Gartner identifies more than 20 solutions in the data marketplace market, covering a wide range of different approaches and use cases. Which solution is right for your organization? Read our 2027 Guide to find out.
The data marketplace is central to delivering on AI priorities by [ 2030 ]
Three statistics explain why 2027 is the right time to invest in a data marketplace.
of organizations are increasing their investment in data management solutions to meet the needs of agentic AI.
Source: IDC, 2026
more likely to have GenAI in production if the organization has the highest level of data product maturity.
Source: IDC, 2025
already have a data marketplace, and 32% plan to adopt one within the next 6 to 12 months.
Source: Gartner, Market Overview for Data Marketplace Solutions, August 2026
"By 2030, data marketplace solutions will be implemented primarily for agentic AI consumption. That means that the solution you choose today will be what your agents rely on tomorrow to better serve your business."
Gartner
Source: Gartner, Market Overview for Data Marketplace Solutions, August 2026
What is a [ data marketplace ]?
A data marketplace acts as a central hub where approved users can securely find, and then shop for data products. Users can do so in a governed fashion for enabling efficient and faster delivery of integrated data products for data, analytics/BI, and AI use cases.
Source: Gartner definition, Market Overview for Data Marketplace Solutions, August 2026.
The data marketplace: a single source of truth for your [ business users ] and [ AI agents ]
Your data management stack produces, stores, documents and transforms data. What it doesn’t do is make that data consumable by your business users or AI agents.
Able to independently discover, request access to, and consume data, with the required usage context to deliver business-relevant answers without hallucinations.
Able to find the right data product through self-service, without requiring support, and consume it based on their access rights and security permissions, ensuring governance compliance—all without requiring technical skills.
The data marketplace complements your existing stack. It connects to your data warehouses, catalogs, integration and BI tools, becoming the single point of data access for both your users and your AI agents. It can also measure data product usage, enabling continuous improvement of your data offering to create business value.
The two categories of data marketplace: [ embedded feature ] or [ stand-alone solution ]
Today’s data marketplace market is divided into two categories: an embedded feature or integrated module within a data platform (such as an integration tool, data catalog or cloud provider) or a dedicated, stand-alone, best-of-breed pure-play solution.
An optional, single-source marketplace designed for data experts
Added as an integrated module or licence option to a catalog, integration tool or data platform from a cloud provider or ISV, the marketplace has a limited scope, particularly when your business users or AI agents need to find data elsewhere. Access is restricted to expert users, and data remains siloed, particularly in large organizations.
A single point of access to all your data
A dedicated, advanced pure-play data marketplace solution, rather than an embedded module within a data platform that is only accessible by your organization’s data experts. It connects to your existing stack while remaining vendor-neutral, integrating with data warehouses, catalogs and BI tools, regardless of provider. Its entire architecture is purpose-built for data discovery, access, and consumption.
[ 5 reasons ] to choose a stand-alone solution over an embedded feature within a data management platform
Gartner recommends complementing your data management platform
with a dedicated, best-of-breed pure-play solution. Here’s why.
Ready for Agentic AI today
MCP server, discovery agent, and management agents. The layer that Gartner expects to be agent-driven by 2030 is already available.
AI components in general-purpose platforms are only advancing in standard data management areas, not around data consumption for business users.
Designed for business users, not just data experts
A browsing experience designed for every employee. It begins with the business need and then works back to the data.
An interface solely usable by data professionals. The marketplace tool integrated into data platforms offers only expert-oriented features, not capabilities designed for business users.
Deep expertise and advanced features
Comprehensive functional scope covering discovery, access, and usage. Deployed in just a few weeks, without requiring a platform project.
A module bolted onto a data platform designed for other needs, such as governance, integration, or lakehouse management. Standard features, with unclear innovation and future development roadmaps.
Vendor-neutral, interoperable, and sovereign
Vendor-agnostic and able to connect to all your platforms, regardless of provider. In a heterogeneous IT environment (multi-cloud, lakehouses, and separate metadata, integration, and data quality tools), Gartner explicitly recommends a stand-alone pure-play solution.
Connectivity focused on data infrastructure rather than the entire IT ecosystem, including data management and business applications. Data leaders risk vendor lock-in, undermining technological resilience and sovereignty.
ROI-driven, focused on value
Internal marketplace, ecosystem data hub, business data apps, and open data portal: one tool for all your data-sharing use cases at scale.
Built to produce and govern data, not to enable its large-scale distribution or measure actual usage.
“A data management platform will never be in a position to deliver best-in-class capabilities across all facets of data management.”
Gartner, quoted in “Building a Successful Data Ecosystem,” Huwise blog
Choose a stand-alone pure-play solution with a [ Usage-Centric ] DNA
"Data and analytics leaders with multiple data management solutions (such as multiple cloud databases, multiple data lakehouses, separate metadata, data integration, and data quality tools) should select a stand-alone data marketplace solution for ease of implementation, integration and interoperability across ecosystems."
Gartner
Source: Selection criterion published by Gartner, Market Overview for Data Marketplace Solutions, August 2026.
They chose Huwise
less time spent searching for data by business users
Reliable data products for business users, through a LinkedIn-like experience for internal data that drives actual adoption and data consumption.
Read the success story
to deploy the marketplace
Brings UKPN’s partner ecosystem together through simple, direct data access for all user types.
Read the success story
customized, one for each subsidiary, and 84 shared data products
A Group-wide data product exchange platform that accelerates cross-functional projects and strengthens synergies across business units.
Read the success story
of data sources centralized in the data marketplace
Makes data sharing a part of every employee’s working life through a data marketplace that makes data easily accessible to all.
of cross-functional data
An internal data marketplace that opens up data access through a GCP connector, a virtualized connector, and AI capabilities.
connected IoT sensors managed
Turn IoT data into a driver of operational performance and large-scale innovation, enhancing both the IoT offering and internal use cases.
Read the success storyHuwise versus 7 other [ stand-alone ] solutions
Source and inspiration: Gartner®, Market Overview for Data Marketplace Solutions, by Richa Jha, Ehtisham Zaidi, and Robert Thanaraj, August 2026.
Assessment based on vendors’ public websites and documentation reviewed on September 23/25 and October 5/8, 2026.
A feature that is not publicly documented may still exist.
Thank you!
Frequently asked questions
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An MCP server is a protocol, not a data layer. It exposes only the capabilities of the system it’s connected to, and only within that system’s scope. Three limitations quickly become apparent with MCP. The protocol doesn’t provide approval workflows, data product–level access policies, or request traceability. Adding more MCP servers means that the agent has to combine partial answers on its own. And nothing in the protocol tells the agent which data products the organization actually uses and trusts. A data marketplace fills these gaps with a catalog of clearly defined data products, associated access rights, business semantics, and usage signals. The protocol transports the data; the marketplace determines what gets delivered.
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Because these tools are designed to produce and govern data, not to make it consumable. When a business user finds what they’re looking for, your data catalog doesn’t provide direct, governed access to the relevant data products. Workday chose to keep its catalog for its 5 million technical assets while making 65 data products available to business users through Huwise. UK Power Networks, meanwhile, runs its data platform and Huwise side by side.
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Just a few weeks, with no upfront data modeling requirements or need to purchase additional tools. This is where the difference between Huwise and other dedicated solutions is most apparent, particularly due to the solution’s flexibility and the agility of Huwise’s onboarding teams.
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Hosting is available in Europe or within your country, depending on your requirements. The platform complies with GDPR and the Data Governance Act, and is ISO 27001 certified. Of the eight dedicated solutions on the market, only four publicly disclose ISO 27001 certification.
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Most vendors don’t publish their pricing. However, pricing models vary by vendor. Usage-based pricing tied to compute consumption charges you for data exploration. Pricing based on the number of data product creators charges you for publishing. Per-user pricing charges you for data adoption, which is the model used by Huwise. Whatever your requirements, get in touch with us to discuss your project.