Data Integration software

Integrate.io is a data pipeline platform. Teams build ETL, ELT, change-data-capture, and reverse ETL flows with a visual builder or through the API, and they can sync SaaS apps without a warehouse in the middle. One subscription covers those motions, so a team does not buy a separate tool for each one.

https://www.integrate.io/

Read reviews of Integrate.io

Fivetran moves data from SaaS apps, databases, and files into a warehouse or lake. The connectors are managed by Fivetran, and transformations can run after the load. It fits teams that want the pipeline running without maintaining the connector code.

https://www.fivetran.com/

Read reviews of Fivetran

Airbyte is an open-source data movement platform. It replicates sources into warehouses and other destinations, including change data capture, and a connector builder covers systems that do not already have a connector. It can run in Airbyte's cloud or on your own network.

https://airbyte.com/

Read reviews of Airbyte

Hevo loads data from SaaS apps, databases, and files into a warehouse. Pipelines are no-code, with transformations before or after the load, and replication can copy everything or only the rows that changed. It is aimed at teams that want the warehouse current without writing the extract.

https://hevodata.com/

Read reviews of Hevo

Matillion builds pipelines into cloud warehouses such as Snowflake, BigQuery, Redshift, and Databricks. A visual job loads and transforms data in the warehouse, and jobs run in that cloud environment. It fits teams that already keep their analytics in one of those platforms.

https://www.matillion.com/

Read reviews of Matillion

Boomi connects business applications and data sources. It automates flows between SaaS apps, databases, and APIs, including movement into analytics systems. It fits when the job is to keep operational systems in sync as well as to feed a warehouse.

https://boomi.com/

Read reviews of Boomi

Rivery builds ELT pipelines from apps and databases into a warehouse or lake. It replicates changes, transforms with SQL or Python, and can push warehouse data back into operational tools. Pipelines are managed, so the team does not run the extract infrastructure.

https://rivery.io/

Read reviews of Rivery

AWS Glue is Amazon's serverless data integration service. It discovers schemas, catalogs data, and runs ETL jobs, including visual jobs, to load data lakes and warehouses. It fits teams that already keep their data in AWS and do not want to manage the pipeline servers.

https://aws.amazon.com/glue/

Read reviews of AWS Glue

Hightouch syncs data from a warehouse into business applications such as a CRM or a marketing tool. The set of records is defined in SQL or a visual model, and a schedule keeps the destination current. It fits when the warehouse is already the source of truth and the job is to activate that data.

https://hightouch.com/

Read reviews of Hightouch

Azure Data Factory is Microsoft's service for copying and transforming data. It connects SaaS apps, databases, and files, and it loads Azure and other destinations. Transformations can run in the pipeline or in the destination. It fits teams already building on Azure.

https://azure.microsoft.com/products/data-factory

Read reviews of Azure Data Factory

Informatica connects and transforms data across applications, databases, and cloud platforms. Its cloud data integration product covers ETL and ELT pipelines, and it sits with Informatica's catalog and governance tools. It fits teams that need the pipeline and a record of where the data came from.

https://www.informatica.com/

Read reviews of Informatica

A data integration tool can sound like a script someone wrote once, but for most teams it is the service that keeps apps, databases, and warehouses in sync.

What is data integration?

Data integration software moves data from the systems that create it to the systems that use it. A pipeline connects a source, such as a SaaS app, a database, or a file, to a destination, such as a warehouse or another app.

Some products transform the data on the way, which is ETL. Others load it first and transform it in the warehouse, which is ELT. Change data capture copies each update as it happens. Reverse ETL sends warehouse data back into the tools people work in. An integration platform can also sync two business apps directly, with no warehouse in the middle.

A low-code builder lets the people closest to the data draw that pipeline. An API lets an engineer create, version, and trigger the same pipeline from code. Both are ways to run one integration product.

Schedules, run logs, and failure alerts are part of the product. That record is how a team notices a broken connector before a report or a downstream app goes stale.

What do data integration solutions move?

They copy and reshape records between sources and destinations. Common jobs include loading a warehouse for reporting, replicating a database, syncing a CRM with a billing system, and pushing a metric back into an operational tool.

Why use a data integration tool?

The biggest reason is that the data arrives without a custom script for every source. A connector maintained by the vendor survives API changes that would break a script the team wrote once and forgot.

• Connect apps and databases without a one-off script
• Keep a warehouse or another system current
• See failed runs before a report goes stale

How to choose

Start with the motion you need. Loading a warehouse is a different job from syncing two SaaS apps. Check whether the product can reach the sources you already have, whether transformations happen before or after the load, and whether the data is allowed to leave your network. A team that both reports and operates from the same records often wants ELT and reverse ETL together.