Best Data Integration Tools: 11 Platforms Compared

Most businesses don't run on one system. Sales data sits in the CRM, orders in the shop, money in the accounts package and support tickets somewhere else again. Getting a single, trustworthy view means connecting them, and doing it by hand doesn't last.

Data integration tools do that connecting for you. The eleven platforms below are listed alphabetically and in no particular order, from tools built for small teams to enterprise suites, and every description comes from the vendor's own site, read this week. For the common traps, see my guide to data integration challenges.

Data integration platforms side by side

In the free plan column, Yes means the tool's own site names a free plan, a free edition, a free account or an open source version. Trial only means a time-limited trial. Not stated means the pages I read named neither, even where there's a button inviting you to try it or book a demo.

Tool	Type	Good for	Free plan
Airbyte	Data movement with hundreds of connectors	Teams wanting a huge connector library	Not stated
Boomi	Integration and data activation platform	Mid-size firms connecting many business apps	Trial only
CData Sync	Continuous data replication with CDC	Keeping data current across cloud and on-prem	Not stated
Estuary	Real-time CDC, streaming and batch pipelines	Mixing real-time and batch data in one tool	Not stated
Informatica	Enterprise data management cloud	Large enterprises with complex data estates	Not stated
Jitterbit	Low-code integration and automation platform	Low-code integration with EDI and APIs	Not stated
Peliqan	All-in-one data platform with built-in warehouse	Small teams without a data engineer	Not stated
Skyvia	No-code cloud data integration and backup	Business users building pipelines without code	Not stated
SnapLogic	Agentic integration platform	Enterprises adding AI agents to integration work	Not stated
Tray.ai	Integration and automation platform for AI	Ops teams automating across many SaaS apps	Trial only
Workato	Enterprise iPaaS and automation	Governing integrations and AI at enterprise scale	Not stated

Eleven data integration tools to compare

Airbyte

Best for: Data teams that want to replicate data from many apps and databases into a warehouse, deployed in the cloud, a private network or on-premises.

Boomi

Best for: Organisations that want one platform to connect business applications, manage APIs and move data, now with data quality tools added.

CData Sync

Best for: IT teams that want data replicated continuously between cloud and on-premises systems, using change data capture to keep it current.

Estuary

Best for: Teams that need change data capture, streaming and batch pipelines in one place rather than running two tools that read the same data.

Informatica

Best for: Large enterprises that want integration as part of a wider data management suite covering quality, governance and master data.

Jitterbit

Best for: Businesses that want low-code integration, EDI and API management in one platform their IT team can run without heavy coding.

Peliqan

Best for: Smaller businesses that want connectors, a built-in data warehouse and reporting in one product without hiring a data engineering team.

Skyvia

Best for: Business users who want no-code data pipelines, reverse ETL and cloud app backup they can set up without writing scripts.

SnapLogic

Best for: Enterprises that want application and data integration alongside tools for building and running AI agents across departments.

Tray.ai

Best for: Operations and IT teams that want to connect SaaS apps, automate processes and govern AI-built workflows from one platform.

Workato

Best for: Large organisations that want integrations, workflows and AI agents built, run and governed from one enterprise automation platform.

What the ICO says about sharing data between systems

The ICO's data sharing code of practice says it demonstrates that the legal framework is an enabler to responsible data sharing, and that it busts some of the myths around it. It also warns that a code of practice isn't a cure for every data sharing challenge.

For an integration project, that's reassuring and sobering at the same time. Data protection law doesn't stop you connecting systems that hold personal data, but you do need to know which data flows where and why. A tool that documents every pipeline and logs every run makes that far easier to show.

ETL, iPaaS and replication: what's the difference?

ETL and ELT tools extract data from apps and load it into a warehouse for reporting. Integration platforms, often called iPaaS, connect apps to each other so a change in one triggers an action in another. Replication tools copy databases continuously, often using change data capture, so the copy stays current.

Some platforms now do all three, and some have added AI agents on top. Decide which job matters most to you first, because a tool built for reporting pipelines can feel clumsy for app-to-app workflows, and the other way round.

Questions to ask before you sign

1. Do you have ready-made connectors for every app we use today?
2. Is the data moved in real time, on a schedule, or both?
3. Can we run it in our own cloud or on our own servers if we need to?
4. Who can build and change pipelines: only engineers, or business users too?
5. How are failed runs reported, and who gets told?
6. Can we see a log of what personal data moved where?

If the jargon is new, our ETL versus ELT guide explains it plainly.

Signs your data needs integrating

• Monthly reports take days. Someone stitches spreadsheets together.
• Numbers don't match. Each team trusts a different system.
• Data is retyped. Orders and contacts are copied by hand.
• Nobody knows the flows. Old scripts run without an owner.

Do you make data integration tools? Tool makers can ask to be considered for a featured place on this list.

My plain advice on choosing a data integration tool

List the five data flows that hurt most when they break, such as orders into the accounts package or leads into the CRM, and test those in a trial. If the tool handles them cleanly with connectors you don't have to build, you're on the right track.

Keep it as simple as your team can support. A small business without a data engineer is better off with a no-code tool it can run itself than an enterprise suite that needs a specialist. If you're connecting your product to a partner's, my integration partner launch checklist covers the practical steps.

Frequently asked questions

What is data integration?

Data integration is the process of combining data from different apps, databases and files so it can be used together, for reporting or to keep systems in sync.

What's the difference between data integration and ETL?

ETL is one type of data integration that extracts, transforms and loads data into a warehouse. Data integration also covers app-to-app connections and real-time replication.

Are there free data integration tools?

Some tools offer free plans or open source versions, and others offer trials. Check the free plan column in the table above and each vendor's site.

What is iPaaS?

Integration platform as a service is a cloud tool for connecting apps and automating workflows between them, usually with ready-made connectors and a visual builder.

Do I need a data warehouse first?

Not always. App-to-app integration doesn't need one. If you want combined reporting across many systems, a warehouse usually becomes the destination.

Is data integration covered by data protection law?

If personal data moves between systems, yes. The ICO's data sharing code says the law enables responsible sharing, but you must know what flows where and why.