15 Best Database Integration Platforms in 2026, Compared

Database integration is connecting data that lives in different databases and systems so it can be used together. In practice it means one of three jobs, and the right tool depends entirely on which one you have:

  • Move data for analysis: copy data from production databases and SaaS apps into a warehouse such as Snowflake or BigQuery (ELT and ETL).
  • Sync systems: keep records consistent between operational systems, such as a CRM, an ERP and a billing database (integration platforms and iPaaS).
  • Use data in place: build apps, dashboards and workflows that read and write several databases directly, without copying anything.

The fifteen platforms at a glance

PlatformJobBest for
Jet AdminUse data in placeApps and workflows across several databases and APIs, no copies
FivetranMove for analysisManaged ELT with many connectors
AirbyteMove for analysisOpen-source ELT
StitchMove for analysisSimple ELT for smaller teams
Hevo DataMove for analysisNo-code pipelines
EstuaryMove for analysisReal-time change data capture
MatillionMove for analysisTransformation in the cloud warehouse
InformaticaMove and governEnterprise data integration and quality
Qlik TalendMove and governIntegration with data quality
Azure Data FactoryMove for analysisMicrosoft Azure pipelines
AWS GlueMove for analysisServerless ETL on AWS
MuleSoftSync systemsAPI-led enterprise integration
BoomiSync systemsiPaaS for mid-size and large companies
WorkatoSync systemsBusiness automation across SaaS apps
ZapierSync systemsSimple app-to-app automations

Use data in place

1. Jet Admin

Jet Admin connects to 200+ data sources, including PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery, Supabase and REST APIs, and builds apps, dashboards and workflows that read and write them directly. You can show orders from Postgres next to payments from Stripe and tickets from Zendesk on one screen, or let a support agent update a record in one system and trigger a workflow in another, without a pipeline or a second copy of the data.

Users are unlimited on every plan. Granular permissions, SSO and audit logs are on the Business plan and above; on-premise deployment is on the Enterprise plan.

Where it stops: it is not an ELT tool. If you need historical data loaded into a warehouse for analytics, use a pipeline tool alongside it.

Move data for analysis

2. Fivetran

Fully managed ELT with hundreds of connectors and automatic schema handling.

Where it stops: usage-based pricing can climb with data volume.

3. Airbyte

Open-source ELT with a large connector catalog, self-hosted or in the cloud.

Where it stops: self-hosting means operating it yourself.

4. Stitch

Straightforward ELT for loading common sources into a warehouse.

Where it stops: fewer advanced features than newer tools.

5. Hevo Data

No-code pipelines with transformations, aimed at smaller data teams.

Where it stops: complex enterprise requirements may outgrow it.

6. Estuary

Real-time pipelines built on change data capture, for low-latency replication.

Where it stops: built for streaming needs; batch-only teams may not need it.

7. Matillion

ETL and transformation designed to run inside cloud warehouses.

Where it stops: centered on warehouse workloads.

8. Azure Data Factory

Microsoft's managed pipeline service for Azure data estates.

Where it stops: strongest inside Azure.

9. AWS Glue

Serverless ETL and a data catalog on AWS.

Where it stops: developer-oriented and tied to AWS.

Move and govern

10. Informatica

Enterprise integration with data quality, governance and master data management.

Where it stops: heavyweight and priced for large enterprises.

11. Qlik Talend

Integration combined with data quality and governance tooling.

Where it stops: a substantial platform to adopt and run.

Sync systems

12. MuleSoft

API-led integration for connecting many enterprise systems.

Where it stops: needs specialist developers and a significant budget.

13. Boomi

iPaaS with connectors, mapping and master data features.

Where it stops: complex mappings still take expertise.

14. Workato

Automation and integration across SaaS apps, with recipes for business teams.

Where it stops: focused on app automation rather than bulk database movement.

15. Zapier

Simple triggers and actions across thousands of apps.

Where it stops: not built for large volumes or direct database work.

Which to use

  • Teams need to work across several databases and APIs, without building pipelines: Jet Admin.
  • Analytics needs data in a warehouse: Fivetran, Airbyte, Stitch, Hevo or Estuary, with Matillion for transformation.
  • You are on one cloud: Azure Data Factory or AWS Glue.
  • Enterprise governance and data quality: Informatica or Qlik Talend.
  • Operational systems must stay in sync: MuleSoft, Boomi, Workato or Zapier.

Frequently asked questions

What is database integration?

Connecting data across databases and systems so it can be used together, by copying it, syncing it or querying it in place.

What is the difference between ETL and ELT?

ETL transforms data before loading it into the destination. ELT loads raw data first and transforms it inside the warehouse.

Do I need to copy data to integrate it?

For analytics, usually yes. For operational apps and workflows, tools that query data in place avoid copies and keep everything current.

What is the difference between integration platforms and ELT tools?

ELT tools move data one way into a warehouse for analysis. Integration platforms sync and orchestrate data between operational systems.

Work across your databases without another pipeline

Start with Jet Admin for free and build an app on several data sources at once.