As 6 melhores ferramentas de integração de dados em 2025

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.

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 at pretty much the same result: connecting 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 apps

• Zapier para orquestração de IA

• Informatica for data quality and governance

• Fivetran for fully managed connectors

• Airbyte for open source extensibility

• Azure Data Factory for Microsoft ecosystem integration

• AWS Glue for AWS integration

What makes the best data integration tool?

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 and transform it to meet the parameters of your target database, warehouse, or lake. But it needs to be able to do this without consuming excessive system resources or creating bottlenecks that slow down your entire data pipeline.

• Ease of use: The best data integration tools are fairly accessible to non-technical users, offering low- or no-code pipeline creation tools, clear documentation, and intuitive interfaces. If an app is difficult to use, it needs to make up for it with some seriously impressive functionality.

• Data quality: Data quality is a measure of how accurate, complete, consistent, and reliable your data is. The tool you pick should do more than just unite data in one place; it should catch and clean up missing values, duplicates, format inconsistencies, and outliers.

The best data integration software at a glance

Best data integration tool for AI orchestration

Zapier (Web)

Prós do Zapier:

• Connects with 8,000+ apps

• No-code automation for non-technical users

• Near-instant deployment

Contras do Zapier:

• More limited data transformation capabilities than traditional data integration tools

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 (analytics software, CRMs, etc.) 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 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 8,000 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, Zapier Agents lets you add AI teammates directly to your workflows to perform data analysis and other tasks without making you switch to a separate platform. If you're already using AI tools on a daily basis but feel like they're siloed away from the rest of your operations, Zapier can bridge those gaps.

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 $20/month for the Pro plan

Best data integration software for data quality and governance

Informatica (Web)

Informatica pros:

• Comprehensive data quality suite

• Scalable for large enterprises

Informatica cons:

• Steep learning curve and complicated interface

• Poor pricing transparency

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 data transformation engine can handle complex business logic that would require custom coding in other platforms—think hierarchical data flattening, advanced lookups, and conditional transformations based on multiple criteria.

For data quality and governance purposes, you get sophisticated matching algorithms for deduplication, standardization libraries for addresses and names, and validation rules for industry-specific formats. And you can lean on Informatica's built-in (and automated) error handling and recovery mechanisms if your data operations ever fail.

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. This isn't a sleek or pretty tool, but it works. Just don't expect a breezy deployment.

Informatica pricing: By request 

Best data integration app for fully managed connectors

Fivetran (Web)

Fivetran pros:

• Over 700 pre-built connectors

• Dedicated support staff

Fivetran cons:

• Muito caro

Fivetran is a super-premium data management platform. It's not exclusive to enterprise-level businesses, but even on its base plan, you're looking at a minimum spend of $500 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, and I doubt the missing 0.1% makes much of a difference. 

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 options 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. 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), starting at $500/month for 1 million MAR

Best data integration tool for open source extensibility

Airbyte (Web)

Airbyte pros:

• Open source with self-deployment option

• Active community

Airbyte cons:

• Limited enterprise features

• Connector quality varies

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 the Cloud plan. It's not free, but its 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.

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.

Airbyte also offers a self-hosted Enterprise plan for larger organizations that want full control over on-premises infrastructure. So, you have to pay for self-hosting (and deal with all the headaches involved) to get access to Airbyte's enterprise features. For that reason, I'd be quicker to recommend this tool to small teams with coding experience.

Airbyte pricing: Free plan available; paid plans vary based on data volume and MAR, starting at $115/month for 10GB of data and 1 million MAR

Best data integration software for Microsoft ecosystem connectivity

Azure Data Factory (Web)

Azure Data Factory pros:

• Seamless Microsoft ecosystem integration

• Hybrid and multi-cloud flexibility

Azure Data Factory cons:

• Limited non-Microsoft connectivity

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 8,000 apps, so you won't be stuck in a bubble even if your tech stack is Microsoft-centric. Learn more about how to automate Microsoft apps, or get started with one of these pre-made workflows.

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:

• Seamlessly connects with Amazon Web Services

• No infrastructure management required

AWS Glue cons:

• Limited integrations with non-AWS data sources

• Costs can ramp up quickly

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 8,000 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, or get started with one of these templates.

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

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, so you can do things like automatically enrich lead records, build custom scoring agents that route high-value prospects directly to your sales team, or manage deals without leaving the apps you're already working in.

Aqui estão alguns exemplos para você começar.

Modelo de Roteador de Leads

Alerte representantes de vendas qualificados com reivindicações ativas e diminua o tempo de resposta dos leads.

Experimente

Mesa de acordo: gerencie aprovações de cotações do HubSpot no Slack

Automatize seu fluxo de trabalho de aprovação de cotações do HubSpot para fechar acordos mais rapidamente e aumentar sua eficiência de vendas.

Experimente

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