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
| Platform | Job | Best for |
|---|---|---|
| Jet Admin | Use data in place | Apps and workflows across several databases and APIs, no copies |
| Fivetran | Move for analysis | Managed ELT with many connectors |
| Airbyte | Move for analysis | Open-source ELT |
| Stitch | Move for analysis | Simple ELT for smaller teams |
| Hevo Data | Move for analysis | No-code pipelines |
| Estuary | Move for analysis | Real-time change data capture |
| Matillion | Move for analysis | Transformation in the cloud warehouse |
| Informatica | Move and govern | Enterprise data integration and quality |
| Qlik Talend | Move and govern | Integration with data quality |
| Azure Data Factory | Move for analysis | Microsoft Azure pipelines |
| AWS Glue | Move for analysis | Serverless ETL on AWS |
| MuleSoft | Sync systems | API-led enterprise integration |
| Boomi | Sync systems | iPaaS for mid-size and large companies |
| Workato | Sync systems | Business automation across SaaS apps |
| Zapier | Sync systems | Simple 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.