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Cloud Data Integration: Tools, Patterns, and When to Use Each

Sean

Platform Writer

Jun 29, 2026
6 min read

Cloud data integration is the layer that moves data between sources and destinations. The right tool depends on three things: the latency the consumer needs, the volume of data, and the transformation the data needs before it lands. The choices in 2026 split into three buckets: ETL, ELT, and reverse ETL.

Cloud Data Integration: Tools, Patterns, and When to Use Each

Table of contents

The three buckets

The three buckets, with the most common use case for each:

  • ETL (extract, transform, load). The data is transformed before it lands in the destination. The right answer when the destination cannot handle the transformation (e.g., a small data warehouse, a database).
  • ELT (extract, load, transform). The data is loaded into the destination first, and the transformation happens in the destination. The right answer when the destination is a modern warehouse or lakehouse that can handle the transformation.
  • Reverse ETL. The data is moved from the warehouse back into the operational systems (CRM, marketing, support). The right answer when the operational systems are the consumers, not the warehouse.

The ETL tools

The ETL tools in 2026, ordered by adoption:

  • Informatica PowerCenter. The enterprise standard. Expensive, mature, full-featured.
  • Talend. Open-source and enterprise-grade. The middle ground.
  • Pentaho. Open-source, the older generation. Still in use at large enterprises.
  • Airbyte. Open-source, the newer generation. The fastest-growing ETL tool.
  • Stitch. Hosted, the simplest. The right answer for small teams.

The ELT tools

The ELT tools in 2026, ordered by adoption:

  • Fivetran. The hosted leader. The right answer when the team does not want to operate the ELT layer.
  • Airbyte. Open-source, with a hosted option. The right answer when the team wants the source connectors to be open-source.
  • dbt (data build tool). The transformation layer. The right answer when the transformation is in SQL and the team wants version control and testing.
  • Stitch. Hosted, the simpler version of Fivetran.

The reverse ETL tools

The reverse ETL tools in 2026, ordered by adoption:

  • Hightouch. The leader. The right answer for the team that wants to send warehouse data back to the operational systems.
  • Census. The runner-up. The right answer for the team that wants a simpler reverse ETL experience.
  • Polytomic. The middle ground. The right answer for the team that wants reverse ETL and operational analytics in one tool.

The streaming tools

The streaming tools, for the workloads that need data in 5 seconds, not 5 hours:

  • Kafka. The standard. The right answer when the team is running a real-time data pipeline.
  • Pulsar. The runner-up. The right answer when the team wants multi-tenancy built in.
  • Kinesis. The AWS managed equivalent. The right answer when the team is on AWS and does not want to operate Kafka.
  • Pub/Sub. The GCP managed equivalent. The right answer when the team is on GCP.
  • Event Hubs. The Azure managed equivalent. The right answer when the team is on Azure.

How to choose

The choice rule: pick the tool the team can actually operate. The team that picks the most modern ELT layer and cannot operate it is in worse shape than the team that picks a simpler batch pipeline and runs it well.

The right starting point for most teams: Fivetran (or Airbyte) for the ELT, dbt for the transformation, and a managed warehouse (Snowflake, BigQuery, Redshift) as the destination. The team can add streaming and reverse ETL as the workload grows.

FAQ

What is cloud data integration?

The layer that moves data between sources and destinations. The right tool depends on the latency, the volume, and the transformation.

What is the difference between ETL and ELT?

ETL transforms the data before it lands. ELT loads the data first and transforms it in the destination. ELT is the modern default because the destination (a modern warehouse) can handle the transformation.

What is reverse ETL?

The process of moving data from the warehouse back into the operational systems (CRM, marketing, support). The right answer when the operational systems are the consumers, not the warehouse.

What is the best data integration tool in 2026?

The right answer depends on the team. For ELT: Fivetran (hosted) or Airbyte (open-source). For ETL: Informatica (enterprise) or Airbyte (open-source). For reverse ETL: Hightouch or Census.

How do I get started with cloud data integration?

Start with Fivetran (or Airbyte) for the ELT, dbt for the transformation, and a managed warehouse as the destination. Add streaming and reverse ETL as the workload grows.

If you are sizing a data integration project, the RunxBuild hosting calculator is the place to model the line items. The pipelines, the destinations, the transformations - each one is a separate number, and the team’s mental model for the project is the sum of those numbers. The RunxBuild dashboard is where the team sees the actual data flow in one place.

#data integration#etl#elt#data pipeline