Three Answers to the Same Question
"How do I get data out of dozens of different systems and into somewhere useful?" is one of the oldest questions in enterprise software, and right now there are three common answers.
Buy a connector marketplace: hundreds of prebuilt pipes, point a source at a destination, done. Buy a unified API: one API surface that normalises an entire category of systems (HRIS, payroll, ATS, accounting) so your engineers write one integration instead of twenty. Or build a governed data product layer that turns whatever lands in your systems into something reusable, access-controlled, and auditable.
These get compared constantly, usually as if they are three flavours of the same thing. They are not. Connector marketplaces and unified APIs both solve connectivity. Only the third solves governance. And once you are putting AI, compliance, or another team's judgement on top of that data, connectivity without governance is the part that quietly breaks everything downstream.
The Connector Marketplace Model
This is the model most people mean when they say "data integration platform." A vendor maintains a large catalogue of prebuilt connectors, Salesforce, Postgres, Stripe, a CRM, a warehouse, and you wire a source to a destination through a UI.
It is genuinely good at what it is built for: getting a pipeline running in an afternoon instead of a sprint. The catalogue breadth is real value, someone else maintains the connector when the source API changes.
What it does not solve is what happens after the data lands. Each pipeline is still a point-to-point pipe. Add enough sources and enough destinations and you are back inside the N x M problem, just with prettier plumbing. There is usually no shared schema across pipelines, no consistent access control on the destination tables, and no single audit trail describing who has actually read what. The marketplace makes moving data easy. It has an opinion about none of the questions that come after.
The Unified API Model
This model comes from a different starting point: not "move data between systems" but "let engineering teams build one integration instead of many." A unified API sits in front of dozens of providers in the same category, say every major HRIS or payroll system, and exposes one consistent API shape over all of them. Build against the unified API once, and you have effectively built against every provider it covers.
It is the right tool for a specific job: product teams embedding third-party integrations into their own SaaS, where the goal is coverage and developer speed, not a persisted, governed asset. The data is usually a pass-through, fetched, used, and gone, not something that gets versioned, access-controlled, or kept for audit.
That is a deliberate trade-off, not a flaw, for the use case it targets. It becomes a problem the moment you need the answer to "who could see this, and can you prove it" six months later, which is exactly the question regulated buyers and anyone shipping AI on top of the data eventually has to answer.
The Gap Both Models Share
Neither model was built to answer governance questions, because neither was trying to. But those are exactly the questions that matter once real decisions, or an AI system, sit on top of the data:
- Who can see this field, specifically? Not "who has access to the destination system," but per-field, per-consumer access control.
- Where did this number come from? Full lineage back through every source that fed it, not just the last hop.
- Can you prove nobody tampered with the record? A tamper-evident audit trail, not an activity log that can be edited after the fact.
- Is the schema a stable contract, or does it silently drift every time a source system changes?
A connector marketplace and a unified API can both move the data. Neither one, by itself, can answer any of those four questions. That gap is exactly what a data product is built to close, and it is why we built Integrius around it rather than around another connector catalogue.
How the Governed Data Product Model Actually Works
Concretely, here is the architecture, not the pitch:
- Connectors normalise, not just move. Sources (Postgres, Salesforce, S3, Kafka, REST APIs, and others) map into a canonical schema per product, not a raw dump of whatever the source happened to send.
- Materialization, not live pass-through. Data lands as a versioned snapshot. That snapshot is the thing you govern, audit, and can reproduce, not a transient in-flight payload.
- Access control is enforced at the point of serving, field by field, not bolted on as a permission over an entire table or connector.
- Every read is logged into a hash-chained audit trail, so "who saw what, when" is provable, not just recorded.
- Aggregates are computed deterministically and precomputed on change, event-driven, not requested fresh from raw rows every time. That matters more than it sounds: it is also why an AI layer reasoning over the result is trustworthy. RAG-style retrieval cannot count; deterministic aggregation over a governed data product can.
The result reads to a consumer, human or AI, as a single governed contract: a schema, an owner, a lineage, and an access boundary, regardless of how many messy source systems fed it.
Comparing the Three Models
| Connector Marketplace | Unified API | Governed Data Product | |
|---|---|---|---|
| Primary goal | Move data fast | One API per category | Governed, trustworthy asset |
| Best for | Ad hoc pipelines, BI feeds | Embedded product integrations | Regulated, audited, or AI-facing data |
| Field-level access control | Rare | No, pass-through | Core to the model |
| Full lineage | Rarely native | No, not persisted | Built in |
| Tamper-evident audit trail | No | No | Yes |
| Data persistence | Depends on destination | Usually none, transient | Versioned snapshots |
| Self-hosted option | Varies by vendor | Rare, mostly cloud | Available |
| Underlying problem solved | N x M connectivity | Category-wide connectivity | Governance and trust |
Which One Is Actually Right for You
None of this makes connector marketplaces or unified APIs the wrong choice, they are the right choice for what they were built for. If you need a dashboard fed from Salesforce by Friday, a connector marketplace is faster than anything else on this list. If you are a SaaS company embedding "connect your HR system" into your own product, a unified API is exactly the right abstraction, you should not be maintaining twenty HRIS integrations yourself.
The governed data product model earns its complexity when the question stops being "can I move the data" and starts being "can I prove what happened to it." That is every regulated industry by default, and increasingly it is anyone putting AI in front of enterprise data, because an AI system that cannot show its lineage is not one you can trust with a real decision.
We built Integrius because we kept hitting that second question with no good answer available. If you are hitting it too, that is the data product governance model worth looking at next.