Comparison
SCIKIQ vs Atlan
Atlan and SCIKIQ are often evaluated together, but they are built to solve different shapes of problem. Here is an honest read on where each one fits.
At a glance
| Atlan | SCIKIQ | |
|---|---|---|
| Primary focus | Active metadata and team collaboration | Unify, govern and activate enterprise data for AI |
| Where data lives | Works alongside your existing integration and storage layers | Data stays in place — no rip-and-replace migration |
| Semantic layer | Typically supplied by your BI or modelling tools | Governed semantic layer and knowledge graph built in |
| AI activation | Delivered through your own AI and analytics stack | Copilot and Agent Factory included in the platform |
| Typical time to first value | Varies with programme scope and integration work | A live 360 view in about 60 days |
What Atlan is built for
Atlan is a modern, collaboration-first metadata platform oriented towards the modern data stack, emphasising active metadata and workflow integration. Organisations that have invested in it usually have a clear, well-scoped mandate and teams who know the product well — and that investment is worth weighing seriously in any comparison.
Where SCIKIQ takes a different approach
SCIKIQ is a single governed layer that unifies data in place, wraps it in a semantic knowledge graph, and activates it through a plain-language copilot and an agent factory. The design assumption is that enterprise data will remain spread across ERP, cloud warehouses and legacy systems, and that the practical problem is giving it shared meaning rather than moving it somewhere new.
That difference shows up most clearly in AI work. Because governed metric definitions and entity relationships live in the platform itself, a copilot or agent resolves questions against defined meaning and traceable lineage instead of guessing from raw tables — which is what makes an answer auditable.
Which should you choose?
Choose Atlan if you are modern-data-stack native, your priority is collaboration and active metadata across tools your teams already use, and you are not looking to consolidate integration.
Choose SCIKIQ if you want governance, semantics, integration and agents in one governed layer over data left where it is, and you need a working 360 view in weeks rather than at the end of a multi-year programme.
The most reliable way to decide is on your own data. A live demo will show exactly how your sources connect and where the governed layer would sit.
Explore further
- Data Governance — metadata, quality and stewardship across every source
- Data Fabric — the knowledge graph and semantic layer in detail
- Data Hub — 187+ connectors, including non-invasive SAP extraction
- Impact studies — what this delivers in production
See it on your own data
A 30-minute live demo, using your sources — not a slide deck.
Frequently asked questions
How is SCIKIQ different from Atlan?
Atlan focuses on active metadata and collaboration across an existing modern data stack. SCIKIQ consolidates integration, governance, semantics and agents into one governed layer, which suits estates with significant legacy and ERP data alongside cloud sources.
Does SCIKIQ work with legacy and on-premise systems?
Yes. Alongside cloud warehouses, SCIKIQ extracts from SAP and other legacy enterprise systems without invasive change, which is often where the hardest enterprise data still lives.
Do we need a separate semantic layer with SCIKIQ?
No. The semantic layer and knowledge graph are core to the platform rather than a separate product, so governed metric definitions are available to BI and to AI from the same place.