Concept card

Live vs Import Connections

As of 2026-09-27

Edited by Cédric Mary, sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

Live vs Import Connections: what is the difference?

The 2026 senior default is live-to-Datasphere-AM for everything — imported models drop DAC inheritance entirely, meaning every story viewer sees every row regardless of permission.

Should I use a live or import connection in SAP analytics cloud?

Use a live connection when the source (SAP BW, S/4HANA, Datasphere, HANA) must keep its security, freshness and row-level authorisations, and its query latency is acceptable. Use an import when you need to blend several sources, plan on the data, or serve users who have no access to the source — accepting scheduled refreshes and SAC-side security. The 2026 default for SAP sources is live to Datasphere; import is the exception you justify.

What it is

Every SAC story binds to data via either a live connection (query-on-render against the source) or an imported model (snapshot copied into SAC at refresh time). The choice determines governance, freshness, performance, and cost — and gets re-litigated on every project. The senior default in 2026: live to a Datasphere analytic model. Everything else needs a documented reason in the ADR.

Live connection economics. Each render queries the underlying analytic model (or BW InfoCube, or HANA Calc View). DAC inheritance flows through automatically; users see only what their permissions allow. Lineage is automatic; the catalog tracks the dependency. Latency = AM query time + network. For governed enterprise reporting, this is the canonical path.

Imported model economics. Data is copied into SAC at scheduled refresh. Render is fast (data is local). DAC does NOT inherit — every user with story access sees every imported row. Lineage breaks at the import boundary. The model goes stale until next refresh. Tolerable only for one-off exploratory analysis on non-governed data.

The 4-axis decision matrix. Governance: live wins (DAC + lineage). Freshness: live wins (always current). Performance: import wins for high-frequency dashboards on small data; live wins everywhere else. Cost: live runs AM queries (CU spend); import copies storage (storage spend) — usually a wash, but live offers better governance per euro.

Why it matters

Import breaks DAC inheritance completely — anyone with story access sees every imported row, a hard fail against GDPR Art. 5 and EU AI Act Art. 10 in regulated domains.
Mixing live-BW and live-Datasphere connections in the same story creates governance drift where users can't tell which dimension is actually governed.
Live wins governance and freshness by default; import only wins on raw render performance for high-frequency dashboards on small, non-governed data.

Key points

Live = governed (DAC + lineage); import = fast but ungoverned
Default 2026: live to Datasphere analytic model
BW migration 1-3 stories/quarter from 2026
Imported tolerable only for one-off exploratory work
Mixed live-BW + live-DSP in one story = drift
DAC re-verify on every rebind
Quarterly connection audit retires unused
Imported flat in regulated domains = GDPR + AI Act fail

Terms used on this page

Live connection: Story queries source on render; data never copied into SAC
Imported model: Source data snapshot copied into SAC at refresh time
DAC inheritance: Row+column permissions flow from source to consumption
Federation: Live query against on-prem or external source via Cloud Connector
Refresh schedule: Cadence at which imported model re-snapshots from source
Cloud Connector: SAP-managed gateway for cloud-to-on-prem connectivity
Lineage: Tracked dependency from source to consumption surface
Catalog connection audit: Quarterly retire-unused review of stored connections

Sources

Full card available to members. What the full card adds: the full decision framework · the SAP vs Snowflake / Databricks / Fabric comparison · the common pitfalls and their fix · the cheat sheet · the architecture schemas · the code blocks · the facts worth quoting.

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