The 8 Best Data Integration Tools in 2026

If you’ve ever had to hunt down an important email across one of your seven inboxes, you know the struggle of having information spread out between a bunch of unconnected systems. Ctrl+F can’t save you when you aren’t even sure where to start looking. Multiply that by hundreds of employees and dozens of systems, and things get real messy.

Data integration tools take siloed data and un-silo it, uniting various data sources into a single master view. This means no more swapping between applications or manually copying and pasting data to a spreadsheet, a few hundred rows at a time.

Different tools handle the integration process differently, but they all aim to connect data sources. To find out which apps do this best, I went through hundreds of user reviews, talked to leaders with firsthand data integration experience, and performed lots of tests of my own. Here’s what I discovered.

The best data integration services

What makes the best data integration platform?

At its most basic level, a data integration tool needs to be able to collect data from multiple sources, move it to a centralized destination, and transform it into a unified, usable format. It sounds simple on paper, but if it were simple, businesses wouldn’t throw wads of money at data integration software that does most of this work for you. 

While different integration tools excel at different use cases and in different tech environments, the best options check these boxes:

• Connectivity: Data integration tools need to be able to pull data from a range of sources, from basic spreadsheets and CRMs to complex analytics and BI software, cloud storage platforms, and SQL databases. The more high-quality connectors a tool has, the better.

• Performance: You want your data integration app to be able to ingest large volumes of data without consuming excessive system resources or creating bottlenecks that slow down your entire data pipeline. For example, it might distribute resource load through AI based on the task.

• Data transformation and quality: A good data integration solution will transform complex datasets to meet the parameters of your target database, warehouse, or lake. For the best data quality, it also needs to catch and clean up missing values, duplicates, formatting inconsistencies, and outliers.

• Data governance and security: I hope this goes without saying, but the tool you pick should protect sensitive information according to industry standards and global laws.

The best data integration software at a glance

Best data integration tool for building safely with AI

Zapier (Web)

Zapier pros:

• Connects with 9,000+ apps

• No-code automation for non-technical users

• Near-instant deployment

Zapier cons:

Most big data integration tools are great for bringing your data together in a central repository, but not always so great if you want to act on that data once it’s centralized. This can lead to situations where you have to manually port integrated data back into your business apps before you actually do anything with it. Zapier solves this problem.

Zapier is an enterprise-level AI orchestration platform with rich data movement, storage, and automation capabilities. Its database tool, Tables, acts as a hub where you can store and manipulate data from all the apps you use, while its governed automation engine pushes insights and updates seamlessly back into those same apps.

I’ll be talking a lot about data source connectors in this article, and Zapier has over 9,000 of them. That’s more than 10 times the number Fivetran offers, to give you an idea of the scale. Chances are, if there’s an app you use that collects data, you’ll be able to connect it to Zapier without writing a single line of code. 

Once you’ve pulled data from your sources into a table, you can set up workflows to do things like automatically enrich that data at regular intervals, transform it into a standardized format, or update coworkers when changes occur through all the other apps in your tech stack.

On top of this, you can add AI steps directly into your workflows to run data analysis, route records, and dynamically take action across your apps. If you’re connecting an AI assistant like Claude or ChatGPT to your data stack, Zapier MCP lets it take action across those same 9,000+ apps directly from your chat window—pulling data, updating records, and triggering workflows without switching tabs. And because Zapier manages OAuth to your connected apps through a single governed layer, your agents never touch raw credentials. You get the breadth of 9,000+ integrations with the safety of knowing credentials stay out of the agent’s hands.

To be clear, Zapier doesn’t have the same data transformation capabilities as an Informatica or an Airbyte, and it’s not designed for heavy-duty ETL (extract, transform, load) scenarios, so you won’t get sophisticated data cleansing algorithms or the ability to process terabytes of data in real time. But what Zapier lacks in transformation depth, it makes up for in agility and connectivity. 

This is the Zapier blog, so don’t just take my word for it. Instead, get a second, third, and fourth opinion by reading some of our customer success stories. 

Zapier pricing: Free plan available; paid plans start at $19.99/month for the Pro plan

Best data integration software for data quality and governance

Informatica (Web)

Informatica pros:

Informatica cons:

Informatica is sort of a dinosaur in the data integration space, but sometimes you need a dinosaur. While newer, nimbler platforms focus on simplicity and speed, Informatica has doubled down on complex data integration functionality. This makes it big, clunky, and a little dated, but also seriously useful for large enterprises.

Make no mistake, Informatica has an overcomplicated interface and a steep learning curve. For that reason, many data engineers have a love-hate relationship with the platform: they wish it was cleaner and more intuitive but also recognize that it puts a lot of tools at their disposal.

Informatica has advanced data profiling that automatically analyzes data quality issues (like null values and format inconsistencies) across your entire environment. Its drag-and-drop data transformation engine includes a massive library of built-in processes, like cleaning, masking, joining, aggregating, and parsing.

With Informatica, you can automatically tackle the most mundane data management tasks with AI. For example, it lets you set data quality rules that kick in at your chosen times, like filling empty Last Name fields every day or correct date formats once a week. And each data catalog entry includes a quality scorecard to help you fix any errors that these rules don’t catch.

For security and governance purposes, you get master data management (MDM) designed for strictly regulated industries. Informatica MDM includes Industry 360 applications with preset security setups for regulated industries. Its healthcare MDM, for example, has data accuracy rates that comply with HIPAA and other standards, like HL7, FHIR, and ICD-10.

Informatica also excels at handling enormous data volumes (like, petabyte-scale) without crashing or running so slowly it may as well be a crash. So, if you need to integrate quality, security-compliant data at scale, you’ll be more than covered.

All this functionality will cost you, though—not only because users say Informatica is very expensive, but also because you’ll likely need to spend time and money training your team to use the software.

Informatica pricing: By request 

Best data integration app for fully managed connectors

Fivetran (Web)

Fivetran pros:

Fivetran cons:

Fivetran is a super-premium data management platform. It’s not exclusive to enterprise-level businesses, but even on its base plan, it’s easy to spend hundreds of dollars per month. On the plus side, you get a fully managed, white-glove data integration service for your money.

This means Fivetran handles connector setup, replication, schema changes, API updates, and maintenance. All you really have to do is configure your destinations and then sit back and watch the data flow. (Though you also have the freedom to control and customize the platform to suit your needs.) Yehor Melnykov, CEO and co-founder of Loio, told me Fivetran’s best feature is “its ‘set it and forget it’ reliability; once it’s running, downtime is rare.” In fact, Fivetran reports 99.9% uptime.

As far as connectors go, you’ll get access to more than 700 on the platform, all of them managed in-house. Users report high connector quality, with updates and fixes going live in a matter of days, often before customers even notice issues.

You get quite a lot of flexibility in how you use these data sources, too. Integration patterns include ELT, ETL, and even a shiny new pipeline called reverse ETL (or rETL) that moves transformed data back into your business apps: CRMs, marketing and analytics software, and tools like Slack, Facebook, and Microsoft 365.

Fivetran also has a proactive customer service team, so you don’t have to subscribe to the Enterprise plan to get on a first-name basis with its support staff. Expect regular check-ins to make sure everything’s running smoothly. 

But still, the cost can be a hard pill to swallow. Plus, if you’re hoping for enterprise-grade cataloging or lineage to go with the high price tag, you’re out of luck. Thankfully, you can preview Fivetran’s low data volume capabilities on its free plan before you reach for your wallet.

Fivetran pricing: Free plan available; paid plans vary based on number of monthly active rows (MAR), connections, and transformations

Best data integration tool for open source extensibility

Airbyte (Web)

Airbyte pros:

Airbyte cons:

Airbyte is the only data integration tool on this list to offer a free, open source option, meaning you can self-host the platform and get full control over your data pipelines at the level of source code. Just be aware that you’ll need a machine that can run a local instance of Airbyte, plus some understanding of server maintenance, security configuration, and Docker.

If you’d rather let Airbyte host, you can jump up to one of the cloud plans. They’re not free, but their volume-based pricing model should still be affordable for small teams and solopreneurs who know (or can at least estimate) their data needs. (You pay by GB of data and number of rows of data to replicate.)

Whether you take the open source or cloud route, you’ll get access to more than 600 pre-built connectors across a variety of databases and warehouses, analytics tools, and other apps like Notion, Google Sheets, and Jotform. You can also add AI agents to your plan that connect to all these apps to update and edit your data.

It’s important to note that Airbyte’s connectors are also open source, so quite a few of them were actually developed by members of the Airbyte community rather than in-house engineers. This isn’t a problem per se, but it does mean you’re at the mercy of devs who don’t work for Airbyte and have no real obligation to test or update their connectors (though someone else can always take up the torch). In other words, quality may vary.

But Airbyte did step up its game for enterprises in the past year. While you used to have to self-host to get access to enterprise features, every plan can now run on the cloud. This means you don’t have to have your IT team deal with self-hosting anymore, but you still have the option to host on your own virtual private cloud if you need to.

Airbyte pricing: Free plan available; paid plans vary based on data volume or compute units, starting at $10/month for one-hour syncs

Best data integration software for Microsoft ecosystem connectivity

Azure Data Factory (Web)

Azure Data Factory pros:

Azure Data Factory cons:

Azure Data Factory (ADF) is a cloud-based data integration tool designed specifically for use with Microsoft apps. A data integration platform built for use with one software ecosystem might sound limiting, but this is Microsoft we’re talking about, and their ecosystem runs deep. 

Thousands of businesses run on Microsoft tech stacks, and ADF seamlessly connects everything from on-premises SQL Server databases to cloud services like Azure Synapse Analytics, Power BI, SharePoint, and Dynamics 365. 

Of course, this means ADF is best for enterprises already invested in the Microsoft stack, particularly if you use Azure Synapse Analytics or Power BI to get data-driven insights about your business. Instead of mobilizing data for analytics using a third-party connector, you can create native pipelines that automatically feed clean, transformed data directly into your Microsoft analytics apps. 

Sure, you could set up similar pipelines using something like Fivetran, but you’d be more likely to run into compatibility, authentication, and data silo issues than if you stick with a single-vendor approach.

ADF has a code-free visual pipeline builder for ETL and ELT, which means even non-technical users can use it to run data integration flows. And despite being a cloud service, it works well for hybrid systems where sensitive data is stored on local servers. 

For non-Microsoft databases, ADF comes with a small number of out-of-the-box connectors to tools like HubSpot, Salesforce, Jira, and Xero. It can even integrate with certain Amazon and Google data sources, though you’ll run into restrictions when it comes to mapping data flows and retrieving metadata. 

Microsoft says you can write custom code to build additional connectors, but devs who use the software say it’s not as code-friendly as they let on, with limitations to script complexity and tricky debugging. 

Still, if you’re already invested in Microsoft tech and want to integrate data sources without hiring a team of coders, ADF should be a solid pick.

Alternatively, you could use Zapier to connect Microsoft tools with all the other software you use. Zapier integrates with more than 9,000+ apps, so you won’t be stuck in a bubble if your tech stack is Microsoft-centric. You can even access and act on all your Microsoft data directly from your AI assistant. Learn more about how to automate Microsoft apps.

Azure Data Factory pricing: By usage; cost varies based on data activity and runtime

Best data integration tool for Amazon Web Services 

AWS Glue (Web)

AWS Glue pros:

AWS Glue cons:

Sometimes, you need a very specific hammer for a very specific nail. If your business primarily runs on the Amazon Web Services (AWS) cloud platform, AWS Glue will be the easiest way to combine and mobilize data from S3, Redshift, Athena, Lake Formation, and other Amazon apps.

AWS Glue’s top feature is its Data Catalog, which is basically a centralized repository for all the data you’ve stored across Amazon software. It works by using crawlers that automatically classify your data by schema and then create metadata (data about your data) that lives in the Catalog and can be used in ETL pipelines.

Glue is pretty much a one-vendor solution to data integration, so it won’t connect seamlessly with most non-AWS databases and software. However, it does support native integration with MySQL, Oracle, Microsoft SQL Server, and PostgreSQL, as well as a range of SaaS tools like Salesforce, Zendesk, ServiceNow, and SAP. For other integrations, you’ll have to lean on (and pay for) third-party connectors (think Snowflake) or write custom code. 

Glue can rack up some hefty costs if you aren’t careful. On paper, the pay-as-you-go model looks fairly attractive, with job prices coming in at under $1 per hour. But it’s also dependent on how many data processing units (DPUs) Amazon uses to run your tasks. When working with large datasets and jobs that run on repeat, Glue gets expensive fast, and some users report being over-allocated with DPUs (which means paying for more processing power than they actually need).

If you do sign up for AWS Glue, Derek Townsend, cloud solutions architect at TierPoint, has some advice: “Start small, run jobs with the minimum resources, track runtimes, and scale up only when you truly need it.”

But I’ll say it again: if your business lives in the Amazon ecosystem, you’ll be hard-pressed to find a better platform than Glue for easy setup, management, and data unification. 

Or you could use Zapier to automate Amazon apps like S3, Redshift, and more by connecting them to the rest of your tech stack. With integrations to over 9,000+ apps, Zapier lets you do things like automatically copy files added to S3 to other cloud storage platforms like Google Drive, Dropbox, and OneDrive. Learn more about Amazon automation.

AWS Glue pricing: By usage; cost varies based on data activity and runtime

Best data integration tool for low-code integration

Boomi (Web, Windows, Linux, macOS)

Boomi pros:

Boomi cons:

Companies that have been around for a while face the issue of integrating data from legacy systems and cloud tech with modern apps. Boomi bridges the gap with a low-code integration builder that connects it all with DIY APIs. The low-code aspect lies in Boomi’s versatility: if you have developers on staff, they can build APIs to their hearts’ content, but non-technical users can still use the drag-and-drop builder just fine.

Boomi’s integration, API management, and data hub modules work together to build data pipelines connected to your apps and systems. They let you drag and drop connectors, AI agents, actions, and logic into a builder or build your own APIs from scratch. You can integrate data from all your systems, whether they’re your on-premises servers or legacy apps like an ancient ERP.

Data transformation happens in the builder’s map steps. While it can’t perform Informatica-level transformations, it covers the bases for most businesses. You can design your own functions or ask Boomi Suggest AI for ideas. Although the more control you want, the more involvement you’ll need from IT.

Boomi protects all your data with enterprise-grade security measures like endpoint authentication and encrypted data transmission. To boot, Boomi is also SOC 2, HIPAA, and FedRAMP authorized—the acronyms you love to see when you need to keep your data private no matter your industry.

In exchange for all of this customizability, you’ll have to invest quite a bit: Boomi doesn’t publicly list its pricing, but our research shows businesses pay five to six figures every year. The juice could be worth the squeeze if you have a lot of budget and complex systems, but probably not so much if you work with simpler tech.

Boomi pricing: Pricing upon request

Read more: Boomi vs. Zapier

Best data integration tool for inventory management systems

Estuary (Web)

Estuary pros:

Estuary cons:

Businesses with more than one inventory management system have a bunch of low-level details, like prices and stock levels, to integrate on a massive scale. Estuary shines at this job thanks to its lightning-fast CDC (change data capture).

CDC is the process of continuously updating your system with data changes. While methods like ETL update in batches, CDC edits your data as updates happen. So, when something ships from your warehouse, for example, Estuary’s CDC can update the number of remaining stock within seconds. 

But much like its parent tool’s namesake—the place where the river flows into the sea—Estuary’s CDC can only update data in one direction. So, in the above example, you wouldn’t be able to have the inventory data also update in your ERP. You’ll need to use ETL for updates between those kinds of apps, but fortunately, Estuary handles it in the same pipeline.

Estuary also offers private and BYOC (bring your own cloud) deployment options for businesses. If you have a cloud environment you like but want to run Estuary, no problem. The same goes for private servers following strict data regulations. 

The main downside: Estuary doesn’t have many connectors for a connector-first platform. It covers big names like Snowflake and Databricks, along with about 200 others, but if you use a more niche data warehouse, you’ll have to build your own connector.

Estuary pricing: Free plan available; paid plans vary by usage

Make your data work for you with Zapier

I’ve already talked about how you can use Zapier to integrate your data into a full AI orchestration platform, but it’s worth highlighting just how much you can do with the data you pull into Zapier.

Zapier integrates data from across your entire tech stack through OAuth-managed connections, so your agents can act on that data without accessing raw API keys or unmanaged integration sprawl. That means you can easily and safely do things like automatically enriching lead records, building scoring agents that route high-value prospects to your sales team, or closing deals without leaving the apps you’re already in.

Related reading:

This article was originally published in September 2025 by Dylan Reber. The most recent update, with contributions from Melissa King, was in July 2026.