Master Data Management Vendor Consolidation Puts More Than Deployment at Risk

Market consolidation is always a cause for angst among customers. Salesforce’s acquisition of Infor­matica and SAP’s acquisition of Reltio have caused real agitation among enterprise users—and under­standably so. I have personally fielded calls from dozens of customers looking to evaluate alternatives, and this topic continues to dominate conversations at industry conferences. Their concerns go deeper than most people realize.

1. Road Maps Built for the Acquirer, Not for You

The most immediate risk is not that innovation slows—it’s that innovation gets redirected. When Salesforce acquires your MDM [master data man­agement] vendor, product investment naturally grav­itates toward Salesforce data, Salesforce integrations, [and] Salesforce use cases. The same applies to SAP. Informatica’s road map will increasingly optimize for Customer 360 and data cloud. Reltio’s road map will increasingly serve SAP master data scenarios.

If your master data serves use cases beyond CRM [customer relationship management] or ERP [enter­prise resource planning]—supply chain, finance, healthcare operations, cross-domain analytics, [and] AI—you are no longer the customer the road map is being built for. The capabilities you need—broader ecosystem integration, open standards, [and] uni­versal consumption across every team and applica­tion—compete for investment against the acquirer’s strategic priorities. History tells us which side wins that contest.

2. AI and Agentic Access Locked Into Closed Ecosystems

Both Salesforce and SAP are building proprietary agentic ecosystems—Agentforce and Joule, respec­tively. These are designed to serve their own products, their own workflows, their own data. As Informatica and Reltio are absorbed, their AI capabilities will nat­urally orient toward powering those vendor-specific agent platforms, providing clean data for Salesforce agents or SAP agents, not for the enterprise’s broader agentic architecture.

This creates a new and underappreciated dimen­sion of lock-in. The pace of change in agentic AI is unprecedented—new agent frameworks, new mod­els, [and] new orchestration patterns are emerging constantly. Enterprises need the flexibility to adopt the best agentic tools regardless of vendor, connect­ing them to governed master data through open standards such as the model context protocol (MCP). Locking agentic data access into a single vendor’s ecosystem is a bet most enterprises can’t afford to make, not when the landscape is shifting this fast.

The enterprises that will succeed with AI are those whose master data is accessible to any agent, any model, [and] any framework—governed consistently, with full auditability—rather than trapped inside a single vendor’s walled garden.

3. Data Products Narrow to Serve Acquirer Personas

Modern enterprises need master data delivered as reusable, governed data products—consumable by every persona across the organization. The data engineer running pipelines in Snowflake, the analyst in [Microsoft] Power BI, the operations team in ERP, and the AI agent querying customer context should all operate from the same governed source.

When an MDM vendor is absorbed into Sales­force or SAP, the incentive structure shifts. Product investment gravitates toward serving acquirer per­sonas—Salesforce admins, SAP developers, their applications, [and] their data models. The compli­

ance team managing regulatory data, the supply chain analyst resolving supplier hierarchies, the data scientist preparing train­ing datasets—they all become secondary. Decentralized, solu­tion-agnostic data product delivery—the capability enterprises increasingly need—is simply not what application vendors opti­mize for.

The risk is that the broad, enterprise-wide consumption model that attracted you to the platform in the first place quietly erodes as investment concentrates on the acquirer’s ecosystem.

4. Deployment Flexibility Disappears

Enterprise customers value deployment choice—on-prem­ises, SaaS, hybrid, or natively within their preferred data cloud. The MDM space once offered genuine options, but consol­idation is narrowing them. Reltio is SaaS-only. There is no on-premises or hybrid alternative, and under SAP ownership, there is no reason to expect that change. Informatica under Salesforce is shifting decisively toward SaaS-first.

For enterprises with data sovereignty requirements, regu­lated data that cannot leave specific jurisdictions, or strategic investments in platforms such as Snowflake or Microsoft Fab­ric, SaaS-only is a disqualifier, not a preference. Extracting data, cleansing it externally, and pushing it back introduces security risks, egress costs, and compliance exposure. Organizations increasingly want master data processing to happen where the data lives—not where the vendor’s cloud happens to be.

The question to ask [is this]: Does your MDM vendor offer genuine deployment choice, or is the migration to their cloud simply a matter of when, not if?

5. Operational Agility Stalls Without DataOps

There is a deeper structural risk that rarely gets discussed. Salesforce and SAP are application companies—their engineer­ing cultures are built around application development cycles, not data operations. Enterprises scaling data management across teams and domains require DataOps discipline: version control, CI/CD [continuous integration/continuous deploy­ment] pipelines, automated testing, and governed promotion workflows. These are not capabilities that application vendors have ever needed to build, and they are unlikely to prioritize them in an acquired platform’s road map.

Without DataOps, every new domain takes as long as the first. Every change carries risk. Scaling across departments means rebuilding the same patterns manually, with no version­ing and no safe rollback. This is the difference between a plat­form that gets harder to manage as it grows and one that gets easier.

6. Cost

Enterprises [that] have taken the time to evaluate alterna­tives are finding they can achieve significant savings by switch­ing. Dependence on a single provider often comes with reduced negotiating power, leaving organizations vulnerable to unex­pected license changes or costly add-ons. When your vendor is owned by a company whose primary business is selling you something else, the pricing dynamics rarely work in your favor.

What to Look For

At the end of the day, these risks share a common root: loss of control over your data strategy. The antidote is a platform built around openness and flexibility rather than proprietary control.

A modern data platform should deliver governed data prod­ucts consumable by every persona—humans, applications, and AI agents alike—through open standards, not vendor-specific APIs. It should offer genuine deployment choice: SaaS, self-hosted, on-premises, or natively within your data cloud. It should operate with software engineering discipline—version control, CI/CD, [and] automated testing—so that scaling across domains and teams becomes faster, not harder. Also, it should provide AI and agentic access that is governed, auditable, and ecosystem-neutral. Now is the time to reassess not just where your data lives, but who governs its future—and whether your platform is built to serve your enterprise or someone else’s.