Data Integration Tools
Data integration tools remain a fundamental architectural component as organizations increasingly seek improved capabilities to support their operational, analytical and AI use cases. This research helps data and analytics leaders make their decisions by analyzing 20 vendors competing in this market.
Market Definition
The market for data integration tools consists of stand-alone software products that enable organizations to combine data from multiple sources and perform tasks related to data access, transformation, enrichment and delivery. They enable use cases such as data engineering, delivering modern data architectures, self-service data integration, operational data integration and supporting AI projects. Data management leaders procure data integration tools for their teams, including data engineers and data architects, or for other users, such as business analysts or data scientists. These products are primarily consumed as SaaS or deployed on-premises, in public or private cloud, or in hybrid configurations.
The common use cases or business problems addressed by data integration tools include:
Data engineering — Data integration by technical user personas to develop, manage and optimize data pipelines, mostly for analytical use cases.
Delivering modern data management architectures — Data integration to deliver modern data management design patterns, such as lake house, data fabric and data mesh, and deliverables, such as data products.
Self-service data integration — Data integration activities by less-technical user personas for various analytical demands of data, such as analytics and business intelligence (ABI), and data science use cases.
Operational data integration — Data integration to implement various operational data integration use cases, such as consolidation of master data, delivery and use of datahubs, interenterprise and partner data sharing, and application integration.
Supporting AI projects — Data integration to support AI projects with complex requirements, such as building chatbots or recommendation systems, and to support delivery of AI-ready data.
Report 2025
Here is a summary of the vendors featured in the Gartner magic quadrant 2025 report.
For the full analysis and detailed insights, you can read the report
here
and view the magic quadrant graphic
here.
| Market Status | Market Vendor |
|---|---|
Leader |
Microsoft |
Leader |
Informatica |
Leader |
Amazon Web Services |
Leader |
Oracle |
Leader |
|
Leader |
Denodo |
Leader |
IBM |
Leader |
Ab Initio |
Leader |
Qlik |
Visionary |
SAP |
Visionary |
SnapLogic |
Visionary |
Workato |
Visionary |
K2view |
Niche Player |
Safe Software |
Niche Player |
Cdata Software |
Niche Player |
Boomi |
Niche Player |
Precisely |
Challenger |
Fivetran |
Challenger |
Matillion |
Challenger |
Confluent |
Report 2024
Here is a summary of the vendors featured in the Gartner magic quadrant 2024 report.
For the full analysis and detailed insights, you can read the report
here
and view the magic quadrant graphic
here.
| Market Status | Market Vendor |
|---|---|
Leader |
Informatica |
Leader |
Microsoft |
Leader |
Oracle |
Leader |
Amazon Web Services |
Leader |
Ab Initio Software |
Leader |
|
Leader |
Qlik |
Leader |
IBM |
Leader |
Denodo |
Leader |
SAP |
Visionary |
Palantir |
Visionary |
SnapLogic |
Visionary |
K2view |
Niche Player |
Precisely |
Niche Player |
Safe Software |
Niche Player |
CData |
Niche Player |
TIBCO |
Challenger |
Fivetran |
Challenger |
Matillion |
Challenger |
Confluent |