Top 15+ Data Integration Tools (Updated for 2023)

Ethan
CEO, Portable

Looking to extract, clean, or synchronize your organization's data?

There are hundreds of ETL pipeline tools out there, but not all are created equal.

We've reviewed the best data integration tools based on their unique features and use cases.

You'll learn about the most important features to look for in a data pipeline tool and how to choose the right connector for your business needs.

What is data integration?

Data integration is the process of moving data from one place to another. Sometimes that's from one data source to another, like keeping the information in your CRM and ERP tools in sync. Other times, that means storing big data in a data warehouse for later use.

There are several types of data integration. These include ETL, manual data integration, and integrations using middleware or common storage.

ETL (extract, transform, load) is a common type of data pipeline that takes data from its original source, cleans and transforms it, and loads it into a warehouse or data lake.

A data integration tool helps you move data from its source to its destination, perhaps performing data transformations between each step.

Here are a few of the most common data integration use cases:

  1. Business intelligence
  2. Machine learning
  3. Legacy system data migration
  4. Software sync

Business intelligence

Data is collected from several apps and loaded into a data warehouse like Snowflake. This single source of truth then feeds into business intelligence tools, analysis software, dashboards, and other platforms to deliver new insights.

Machine learning

Large amounts of data from one or more apps are loaded into the cloud, either in a batch or continuously. The data trains machine learning algorithms using real-time, real-world information.

Legacy system data migration

Many organizations still rely on legacy on-premise systems but want to begin the transition to modern cloud-based web services. Data integration tools can ensure a smooth transition or continually update for organizations that plan on using both systems in parallel.

Software sync

Data from two platforms is collected, cleansed, and synced. A common use case would be synchronizing client information across marketing and sales software, like matching newsletters subscribers in Mailchimp with prospects in Salesforce.

Here's what to look for in a data integration tool

Choosing the right data connector is an important decision. You'll want to look for the following factors:

Data sources.

The best tools have a broad range of pre-built connectors that integrate with the most important data sources and destinations you need. Only choose a tool that lets you access data necessary

Extensibility.

Chances are, no single platform will have built-in integrations with all the long-tail sources you need. In that case, consider where you'll get connectors for your missing sources. Will the team develop them? Will you be able to develop them in-house?

Pricing model.

Many integration tools use a consumption-based pricing model, which can vary every month. Others charge per data workflow, which provides a consistent price.

Support.

If something goes wrong, will you have help when you need it? There's a good chance the APIs your integration depends on will change from time to time. Will the platform handle this maintenance?

You'll also need to decide on a few different options.

Ease of use vs. customizability.

Most integration tools are either user-friendly or highly customizable. For non-technical teams, a no-code platform might be the best choice even though it might not offer the most powerful options. A highly experienced team, however, might want more features that a code-only tool offers.

On-premise vs. cloud-based.

Most modern data sources are in the cloud, so choosing a cloud-based data integration platform makes sense. But if you want more customizability for the integration, an on-premise tool can make sense.

Proprietary vs. open-source.

Most SaaS data integration tools are proprietary. They require less maintenance but cost money each month, and you won't be able to adapt the software. Open-source tools let you make changes and are usually free, but require you to manage all overhead like servers, updates, security, and more.

Batch vs. real-time processing.

Most data can be handled on a regular schedule, like at the end of each workday. But other data types need to be updated in real-time, like transactions and inventory. Most tools are best at one or the other.

What are the best data integration tools?

We've reviewed the major data tools, platforms, and vendors. The following are the best data integration tools for this year.

Top 15 data integration tools:

  1. Portable

  2. Informatica

  3. Talend

  4. Dell Boomi

  5. Jitterbit

  6. SnapLogic

  7. Integrate.io

  8. Oracle

  9. Pentaho

  10. Hevo

  11. IRI Voracity

  12. SAP

  13. ZigiOps

  14. Microsoft

  15. IBM

1. Portable

Portable is the best data integration tool for teams with long-tail data sources.

Portable is an ETL/ELT platform that features connectors for 300+ hard-to-find data sources.

The Portable team will develop and maintain custom connectors on request, with turnaround times as fast as a few hours.

Key features

  • 300+ built-in data connectors.

  • Fast turnaround time for custom connectors.

  • Ongoing maintenance of long-tail connectors at no additional cost.

Best suited for

Portable is best for teams that need to connect several data sources and want to focus on gleaning insights from data instead of developing and maintaining data pipelines.

2. Informatica

Informatica is a portfolio of high-performance data virtualization tools. It includes features for data governance, integration services, application integration, analytics, and more.

Key features

  • Comprehensive suite of tools including Informatica PowerCenter, Informatica B2B Data Transformation, and more.

  • Cloud-based and on-premises deployments available.

  • Advanced data transformation functionality.

Best suited for

Informatica is best for enterprise businesses looking for a robust, comprehensive solution for all kinds of data needs.

3. Talend

Talend is a platform with no-code options for data transformation and ETL. It has a forever free plan, but with limited features and self-service support only.

Key features

  • Comprehensive cloud data integration.

  • Integration with all major cloud platforms.

  • Connectors for Hadoop, NoSQL, IoT, machine learning, Spark, and more.

Best suited for

Talend is best for teams that need an all-in-one platform for data connectivity and analysis.

4. Dell Boomi

Dell Boomi is a low-code tool that works on public clouds, private clouds, and on-premise deployments. It uses a graphical user interface, automation, and a unified reporting portal.

Key features

  • Support for real-time data integration.

  • Endpoint connectors for public and private clouds.

  • Designed for speed with an architecture built for faster connections.

Best suited for

Dell Boomi is best for leveraging data across hybrid infrastructures.

5. Jitterbit

Jitterbit is an integration platform-as-a-service (iPaaS) for SaaS and on-premise applications. It uses artificial intelligence technology to automate endpoints.

Key features

  • Works for cloud-based and on-premise data flows.

  • AI engine for a more efficient data integration process.

  • Automapper feature with 300 prebuilt templates to speed up the data transformation process.

Best suited for

Jitterbit is best for enterprises that need a single tool for the full data lifecycle.

6. SnapLogic

SnapLogic is a data integration solution that uses artificial intelligence to create automations. It uses a drag-and-drop visual platform that doesn't require code.

Key features

  • Support for cloud applications, big data, and IoT integrations.

  • Real-time data integration capabilities.

  • Integration with Hadoop and other NoSQL data sources.

Best suited for

SnapLogic is best for non-technical teams that need an integration tool that doesn't require code.

7. Integrate.io

Integrate.io is a data integration platform that supports ETL and ELT workflows. It offers integration services for cloud platforms and on-premise data.

Key features

  • Offers for no-code and low-code cloud data integration.

  • Universal REST API connector for easier data ingestion.

  • Supports transformations between internal databases and cloud warehouses.

Best suited for

Integrate.io is best for teams who need a powerful platform that doesn't require code.

8. Oracle

Oracle has a suite of tools for data integration, including Oracle Data Integrator and Oracle GoldenGate. The platform includes data governance and profiling features.

Key features

  • Fully integrated into the Oracle ecosystem of tools.

  • Auto-detection of corrupted data and built-in corrective transformations.

  • Machine learning and AI capabilities.

  • Metadata extraction.

Best suited for

Oracle is one of the most cost-effective solutions for enterprises that need a data integration solution for massive amounts of data. It's also the easiest solution for businesses fully integrated into the Oracle ecosystem.

9. Pentaho

Pentaho is a platform now owned by Hitachi Vantara that provides a range of tools for data operations. It's focused on batch processing for data management and analytics.

Key features

  • Supports data replication for unstructured data

  • Focused on big data applications.

  • End-to-end analytics reporting data.

Best suited for

Pentaho is best for teams that need a big data tool for on-premise or cloud data integration handled in batches.

10. Hevo

Hevo is a data replication and ETL tool for near real-time data processes, including SaaS data sources and on-premise databases.

Key features

  • Support for major data warehouse destinations including Snowflake, AWS Redshift, and Google BigQuery.

  • Automatic schema detection.

  • Automated data pipelines with 100+ pre-built connectors.

Best suited for

Hevo is best for teams looking for an automated data pipeline that can automatically detect schema for new data sets.

11. IRI Voracity

IRI Voracity is an ETL tool that handles data cleansing for structured, semi-structured, or unstructured formats.

Key features

  • Data validation and enrichment capabilities.

  • Robust features for governance and data quality.

  • Features for personally identifiable information (PII) masking and synthetic test data.

Best suited for

IRI Velocity is best for teams that need extensive data cleansing and governance capabilities.

12. SAP

SAP is a suite of tools including SAP Data Integrator, SAP Cloud Platform, and more. It integrates with other SAP products like its flagship ERP platform.

Key features

  • Management of cloud-based and on-premise data.

  • Complete platform for integration, quality, cleansing, and integration.

  • Efficient batch processing for big data workflows.

Best suited for

SAP is best for users familiar with the SAP suite of data products.

13. ZigiOps

ZigiOps is a data integration service to streamline data workflows across different types of data. It offers no-code features and real-time data integration.

Key features

  • Smart data loss prevention.

  • Works for enterprise data in the cloud and on-premise.

  • Functionality for deep integrations, mapping, and filtering.

Best suited for

ZigiOps is best for teams looking to automate as many data integration services as possible.

14. Microsoft

Microsoft has several data services in its suite of tools, including Azure Logic Apps, Microsoft Flow, and SQL Server Integration Services (SSIS).

Key features

  • Built-in support for Microsoft SQL Server and Azure Data Factory.

  • Scalable, pay-as-you-go service.

  • Easy data mapping without a steep learning curve.

Best suited for

Microsoft's data integration tools are best for companies with deep integrations with Azure or other tools in the Microsoft ecosystem.

15. IBM

IBM has several data tools, including InfoSphere DataStage and App Connect.

Key features

  • Massively parallel processing capabilities.

  • Robust data quality features, including profiling, matching, enrichment, and standardization.

  • Support for cloud-based and on-premise data sources.

Best suited for

IBM's suite of data integration tools is best for teams already using IBM tools in other areas.

The botton line on data integration tools

Choosing the right data integration tool can help your business grow, or it can slow you down. There are plenty of options on the market, and each has its strengths and weaknesses.

Depending on whether you're looking to warehouse big data for machine learning or business analytics, synchronize separate systems, or something else, there's a data solution tailored to your needs.

Most importantly, choose a tool that integrates with the data sources you need and works with your current systems. Portable handles all development, maintenance, and troubleshooting for you, so your team can focus on using your data---not moving it around.