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DatascaleIntegrationsData Integration & ETL

Category

Data Integration and ETL: Pipelines, Not CSV Exports

Four tools that move marketing data into the warehouse and keep it in shape, Fivetran to dbt. Rated from running pipeline projects.

4 integrationseditorially ratedas of June 2026
dbt

dbt Labs

Self-hosted

Transformation layer for the warehouse. Versioned, tested SQL models with lineage instead of SQL sprawl across BI tools.

4.3
Details →
Fivetran

Fivetran

EU region

Managed-ELT heavyweight with 750+ connectors. Reverse-ETL native since the Census acquisition, end-to-end data movement from one place.

4.3
Details →
funnel.io

Funnel Oy

Managed

Marketing data hub with 600+ connectors. Harmonises marketing data before BigQuery / Snowflake so BI and AI layers get a clean schema.

4.3
Details →
Airbyte

Airbyte

EU region

The open-source challenger to Fivetran. A massive ecosystem of community connectors for long-tail APIs, but requires more day-to-day maintenance and babysitting.

4.0
Details →

Back to the catalog →

Head-to-head

Data Integration & ETL side by side.

Score, rating axes and facts for every rated tool in this category, next to each other. Drop columns and add them back.

4 of 4 tools · Data Integration & ETL

Criterion
dbtSelf-hosted
FivetranEU region
funnel.ioManaged
AirbyteEU region
Overall score
4.3
4.3
4.3
4.0
Ecosystem
4.7

De-facto standard of the transformation layer with a broad package landscape. Since 1 June 2026 dbt Labs belongs to Fivetran, so the transformation layer is no longer independent of the loading vendor.

5.0

Over 750 sources and more than 200 destinations, including reverse ETL since the Census acquisition. Since the dbt Labs merger closed on 1 June 2026, the transformation layer belongs to the same vendor.

4.5

Over 600 connectors, including long-tail ad platforms; the Starter tier covers 121 of them.

5.0

A huge community connector landscape deep into the long tail.

Reliability
4.5

Tests on every build catch silent data errors before they hit a dashboard.

4.5

The managed heavyweight: pipelines run without babysitting.

4.5

Managed pipelines that simply keep running.

3.0

Community connectors vary in quality, plan for maintenance.

Value for money
4.5

dbt Core is open source; costs only start with Cloud or orchestration.

3.0

MAR-based pricing gets expensive at scale.

3.5

From mid-size volumes the licence becomes a real line item.

4.5

Open source and self-hosted, far cheaper than managed ELT.

Ease of use
3.5

Assumes SQL and git discipline, otherwise the value stays on the table.

4.5

Pick a connector, choose a destination, done.

4.5

No-code harmonisation, marketing teams manage without engineering.

3.5

Setup and upkeep need a team that runs pipelines.

Pricing model
Core free; Cloud per user
Usage-based (monthly active rows)
Subscription by data volume
Open source; usage-based cloud
Vendor
dbt Labs · USA
Fivetran · USA
Funnel Oy · Sweden
Airbyte · USA
Subcategory
Transformation
Ingestion & Connectors
Ingestion & Connectors
Ingestion & Connectors
Operating model
Self-hosted
EU-Region
Managed · EU
EU-Region
Last reviewed
May 2026
May 2026
May 2026
Jun 2026
When it fits
When SQL transformations should be versioned, tested and documented.
When you want a broad, managed connector portfolio and end-to-end data movement from one vendor.
When marketing data from many sources should flow harmonised into the warehouse.
When long-tail APIs need connecting and engineering capacity exists to run it.
When it does not
When there is only one report and nobody maintains SQL.
When only marketing data counts. Then a focused tool like funnel.io is leaner and cheaper.
When only two or three standard sources count; then native exports cost less.
When nobody wants to babysit pipelines; then Fivetran or funnel.io.

Every value comes from our individual reviews, scored against the review methodology. Prices without warranty, no paid placement.

Data integration connects source systems to the warehouse: ads platforms, shop, CRM, analytics. ETL tools replace what otherwise ends as a CSV export with copy-paste, using versioned, monitorable pipelines.

When this category matters

As soon as one report regularly needs data from more than one source. During any marketing-warehouse build anyway. And at the latest when an API update has silently broken a home-built pipeline for the third time.

Decision criteria

  • Connector coverage for your concrete sources, not the catalog length.
  • Cost model: by active rows, data volume, or self-operation.
  • Operating responsibility: managed SaaS or self-hosted with ops effort.
  • Transformation layer: loading raw data is not enough, models must be testable.

Common stack combinations

Fivetran or Airbyte, what is the core difference?

Fivetran is managed and gets expensive at high row volume; Airbyte is open source with a self-operation option. The real question is usually licence budget versus ops capacity.

Why does a pipeline need dbt on top?

Pipelines deliver raw data; dbt turns it into tested models with naming conventions, tests, and documentation. Without that layer, every dashboard becomes a one-off build.

Tool decision

Which tool fits your situation.

The Stack Calculator gives you a first direction; the Audit Sprint decides with numbers from your own traffic.