Businesses today are adopting more and more SaaS apps, and there is no indication that this adoption will slow down anytime soon. Without a dedicated toolset to connect all the apps to dashboards, storages, and each other, it will soon become impossibly tedious to get timely insights from your company's data.
What data integration tool (or tools) your company adopts is therefore one of the most important tooling choices it can make.
Before we present the shortlist of our favorite data integration tools, let's take a quick look at how the vendor landscape is evolving and what you should look for when choosing a data integration tool that will be relevant to your use case in 2024 and beyond.
Or, simply click to skip down to the tools.
What to Look for When Choosing a Data Integration Tool
In short, a modern data integration tool should:
- Be able to connect any source to any destination (be end-to-end).
- Have an extensive portfolio of connectors.
- Provide a centralized overview for governing all integrations.
- Offer inbuild data quality and logging solutions.
- Have a user-friendly interface.
- Be highly customizable.
- Be fully scalable.
- Be transparently priced.
- Be Soc 2 Type II certified, among other security criteria for data tools.
- Not have too much functionality that overlaps with other tools.
As indicated by this list, most data integration tools today do more than just move data. Some have inbuilt analytics functionality, some have data storage functionality, some have inbuilt data quality and observability mechanisms. Some are cheap, some are expensive. Some specialize in one or two types of integration, while others do it all.
When choosing a data integration tool, here are some important considerations. Click the arrows to unravel details.
What Data Integration Types Do You Need Now and in the Future?
The market is currently filled with specialized integration tools for every use case—event-based messaging tools, ETL and ELT tools, database replication tools, and reverse ETL tools.
Traditionally, having these specialized tools for different use cases has made sense. Now, this is changing.
To ensure that you don't have to keep adopting more specialized tools in the future that support new integration types, it makes the most sense to have a single, end-to-end integration tool that supports all key integration types.
As data and analytics become a bigger and bigger part of everyday work, it will become less and less practical to have several niche tools for different workflows.
For example, when data teams want to integrate data from multiple eshops in a data warehouse, they won't want to use one tool for ETL, another for reverse ETL, and another to fire events in between apps and a CRM for the sales team. It will be much easier if they can just use a single tool to manage all integrations, regardless of where they sit in a data infrastructure.
How Willing Is the Vendor to Develop New Connectors and How Fast?
Future-proofing is not just about enabling multiple integration types; it's also about willingness to develop new connectors quickly. Indeed, a service may have all the connectors you need today, but what if you start using services they don't support?
Will you have to build and maintain new connectors yourself? Will they build it for you, but in six months? You want a vendor who is willing to build what you need, when you need it.
How Customizable/Flexible Is the Data Integration Solution?
Out-of-the-box solutions are absolutely essential for any organization that doesn't want to accept the Sisyphean task of building and maintaining its own data integration solutions. But, let's face it—data-mature organizations are going to want stuff customized. How willing is the vendor's support team to work with you to implement custom transformations or connect custom datasets, including from proprietary tools?
Read some online reviews or, better yet, sign up for a free trial and talk to support directly.
Does the Tool Enable Direct Connection of Apps to BI Tools?
If you're searching for a data integration tool, you're likely on a data team. But what about the people on your business teams who want to connect, let's say, Facebook Ads data directly to Looker Studio?
More and more, line-of-business professionals will want to make direct connections like this, so that they can analyze data independently for ad hoc insights.
In addition to ETL, reverse ETL, database replication, etc. for data teams, it would be well to choose a data integration tool that lets non-technical teams serve themselves.
Tools that tick this box will inevitably have a no-code interface and be easy to use.
Does the Tool Have Any Inbuilt Analytics or Storage Capabilities?
Any integration tool that can connect data directly from SaaS apps to BI/dashboarding tools will inevitably have some kind of (at least temporary) storage system, which is perfect for companies that don't yet have a data warehouse.
Some data integration tools also have native analytics capabilities. This can be a good thing for teams/organizations that need a single data solution to ingest, store, and visualize data. However, buyer beware—tools like this may be a nice quick fix for their target audience (e.g. marketing or ecommerce teams), but for organizations wanting to build a future-proof data infrastructure, they are not ideal.
Why? Because inbuilt analytics functionality almost always comes with a significantly higher price tag, and the visualization capabilities of such tools almost always pale in comparison to those of dedicated analytics tools. So, as you develop your data infrastructure, you'll likely find yourself paying extra for something that isn't as good as the real thing.
What Data Quality Solutions and Observability Mechanisms Does the Tool Offer?
Data quality is a consistent roadblock to the success of data initiatives, especially AI initiatives. And it will only become a bigger problem as we continue to collect more and more data.
To handle this challenge, most organizations that take data quality seriously will need a dedicated data quality solution on top of their database(s). Still, data integration tools can do much to reduce data quality challenges by solving essential quality problems right at the extraction level.
Format harmonization, anomaly detection, rule-based filtering, detailed error notifications—these are some of the data quality features that will save processing and troubleshooting in downstream systems.
Observability goes hand in hand with data quality because it helps streamline problem-solving processes and, in general, makes managing data easier. Make sure you choose a data integration tool that gives you access to detailed logs and lets you manage all data connections via a central view.
Top Data Integration Software for 2024 and Beyond
Every tool here provides multiple integration types and—depending on the needs of a given organization—can be an invaluable component of a future-ready data stack.
Here is a bird's-eye view of which tools offer which integration types.
Now, let's zoom into the details.
1. Dataddo
Dataddo is a fully managed, no-code data integration platform that connects cloud-based applications, BI tools, data warehouses, and data lakes. The platform offers ETL/ELT, reverse ETL, and data replication functionality, as well as an extensive portfolio of connectors, enabling business professionals with any level of technical expertise to send data from any source to any destination.
Key features:
- Pricing: Fixed (pipeline/flow-based). Free plan available.
- Supported integration types:
- ETL/ELT
- Database replication
- Reverse ETL (app -> app)
- Event-based integration (app -> app)
- Apps -> BI tools (end-to-end)
- Headless data integration
- Data quality features: Transformations, rule-based filter, monitoring, detailed logs (thanks to Dataddo connector).
- Encryption: In-transit and at-rest.
- Time to add new connectors: 10 business days (free of charge).
- Security: SOC 2 Type II certified, ISO 27001 compliant.
2. Hevo
Hevo is a cloud data integration platform specializing in ETL to a select number of popular data warehouses. Additionally, it provides capabilities for database replication and supports reverse ETL to Salesforce and HubSpot CRMs only.
Key features:
- Pricing: Variable (event-based). Free plan available.
- Supported integration types:
- ETL/ELT
- Reverse ETL (only to HubSpot and Salesforce)
- Database replication
- Data quality features: Transformations, monitoring. Logs via Amazon CloudWatch Logs.
- Encryption: In-transit and at-rest.
- Time to add new connectors: Unknown.
- Security: SOC 2 Type II certified, ISO 27001 compliant.
For additional info, see a detailed comparison of Hevo and Dataddo.
3. Integrate
Integrate is tailored for ecommerce companies, and therefore features a no-code interface, but also offers powerful tools for data specialists. It supports various data integration types, yet lacks direct application-to-BI tool connections—a common requirement for ecommerce professionals who need ad hoc insights.
Key features:
- Pricing: Fixed (based on tiers & connectors used).
- Supported integration types:
- ETL/ELT
- Reverse ETL (app -> app)
- Database replication
- Headless data integration
- Data quality features: Transformations
- Encryption: In-transit and at-rest (premium feature).
- Time to add new connectors: Unknown.
- Security: SOC 2 Type II certified, ISO 27001 compliant.
4. Fivetran
Fivetran is a cloud-based integration solution with a key distinction from the solutions above—it focuses only on ELT and data replication (no ETL). This makes it suitable for companies that need to get all their data to a warehouse fast, and that have the engineering resources to clean it once it gets there.
Key features:
- Pricing: Variable (row-based). Free plan available.
- Supported integration types:
- ELT
- Database replication
- Headless data integration
- Data quality features: Notifications, a "history" mode for analyzing how data has evolved, log data kept for 1 week.
- Encryption: In-transit and at-rest.
- Time to add new connectors: Must be coded by users.
- Security: SOC 2 Type II, ISO 27001 certified and/or compliant.
For additional info, see a detailed comparison of Fivetran and Dataddo.
5. Talend
Talend is an end-to-end data integration platform for businesses of all sizes that offers both open- and closed-source solutions. It offers a user-friendly interface, a comprehensive toolset for ETL/ELT, and is most suitable for businesses that have a hybrid cloud-on prem data infrastructure (because cloud-native support is limited). The only core integration type it doesn't offer is direct app-to-BI-tool connection.
Key features:
- Pricing: Fixed (user-based).
- Supported integration types:
- ETL/ELT
- Database replication
- Reverse ETL (app -> app)
- Event-based integration (app -> app)
- Headless data integration
- Data quality features: Transformations, data profiling, filtering, and comprehensive monitoring and logging options.
- Encryption: In-transit and at-rest.
- Time to add new connectors: Talend offers a DIY connector builder tool.
- Security: SOC 2 Type II, ISO 27001 certified and/or compliant.
6. Informatica
Informatica's Intelligent Data Management Cloud is a big-guns, end-to-end enterprise data integration solution that supports a diverse range of data integration use cases. It can do just about anything, but it doesn't connect SaaS apps directly to BI tools (at least not out of the box).
Key features:
- Pricing: Various models (consumption-based).
- Supported integration types:
- ETL/ELT
- Database replication
- Reverse ETL (app -> app)
- Event-based integration (app -> app)
- Headless data integration
- Data quaity features: Transformations, profiling, pre-built rules, notifications, logs.
- Encryption: In-transit and at-rest.
- Time to add new connectors: Informatica offers a DIY connector builder tool.
- Security: SOC 2 Type II, ISO 27001 certified and/or compliant.
Summing Up: Choosing a Data Integration Solution
As we said at the beginning of this article, it's extremely important to pick a single tool that can handle all integrations you need now or might need in the future. This means that it should be both "out-of-the-box" and customizable. For best effect, you'll also want it to have inbuilt data quality tools that help eliminate as many problems as possible before the data hits its destinations.
You'll also want a tool that doesn't offer mandatorily paid functionality that you may not need in the future (we're thinking specifically about tools with inbuilt analytics capabilities). By the same token, you'll want a tool that offers optionally paid functionality that you can upgrade to in the future without breaking the bank.
Lastly, you'll probably want a tool with a user-friendly interface that lets your non-tech teams like marketing and sales connect online services directly to dashboarding apps, so that they can get quick insights whenever they need, without bothering the data team.
Oh yeah, security is a top priority, too. But, as far as the tools on this list are concerned, that shouldn't be a concern 😊
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