Introduction

Organizations of all sizes and industries are looking for ways to enact digital transformations within their business, using new technologies to outperform their rivals and better serve their customers.

For these forward-thinking companies, big data has become an essential concern: the average company now manages 163 terabytes (163,000 gigabytes) of data. However, all this information is of little use without a strategy for effectively managing and integrating it to get valuable data-driven insights.

According to a study by the consulting firm McKinsey & Company, data-driven organizations are 23 times more likely to acquire new customers and 19 times more likely to be profitable than their competitors. It’s no wonder that 99 percent of executives say that they are working to build a data-driven culture in their organization. 

Still, too many companies don’t know how to take advantage of all this information, or simply don’t have the technical chops. Data integration is a greater challenge than ever before: more data sources, new data types, and hybrid cloud and on-premises environments all present serious challenges. A survey by the software company Progress finds that data integration is the number one challenge for digital transformation.

The good news is that businesses who need data integration tools have a wide variety of alternatives at their fingertips. But how can you sort through all these data integration software options to find the right one for your needs and objectives? In this article, we’ll discuss some of the most popular data integration tools, and how you can select the best data integration tool for your situation.

Table of Contents:

Data Integration: Definition

How to Choose the Right Data Integration Tool

The Top Data Integration Tools

Conclusion

Data Integration: Definition

As the term suggests, “data integration” refers to the act of collecting and combining information from multiple sources for the purposes of analysis and reporting. These sources may include sales and marketing data, customer support statistics, financial projections, and more.

The value of a single data point is next to nothing—information becomes exponentially more useful the more you have of it. Data integration allows you to see the big picture and find hidden insights that would otherwise go undiscovered.

Information may exist in many different formats and structures within your business. During the data integration process, this information needs to be standardized and unified. The final step is to migrate this data from disparate sources into a data warehouse or data lake, where it can be more easily accessed and analyzed.

One of the most important use cases for data integration is for companies to better understand their customers. Information from across the business—including finance, sales, marketing, research and development, production, and support—can help you better understand what your customers want and how you can provide it at maximum efficiency.

How to Choose the Right Data Integration Tool

There are more data integration tools than any one company could possibly need or use, so you’ll have to choose your data integration software judiciously.

Adopting a “one-size-fits-all” approach is the wrong way to go about it when choosing a data integration tool. The issues to take into account here include:

  • Your company’s situation: Different tools for data integration are better suited for companies of different sizes or industries, depending on the amount and the type of data you hold. Remember that as your business grows, so too will the volume and the complexity of the data you store.
  • IT infrastructure: The constraints of your IT environment could mean that you prefer a cloud-based or an open-source data integration solution. Whether your data is stored on-premises or in a hybrid cloud setup, make sure that your data integration tool of choice is capable of working with it.
  • The types of data sources and applications: According to an estimate by Forrester Research, companies use an average of 66 different SaaS (software as a service) applications. However, not all data integration tools are capable of working with all data formats and applications.
  • Regulatory and compliance issues: Companies in certain industries such as finance, healthcare, and retail need to comply with regulations such as Sarbanes-Oxley, HIPAA, and PCI-DSS that govern how they store and treat sensitive private data. If this concern applies to you, make sure that you select a data integration tool that is compliant with all necessary laws and standards.

The Top Data Integration Tools

Now that you know what to look for when selecting a data integration tool, what are the solutions you have to choose from? In this section, we’ll go over your options in more detail by discussing some of the best data integration tools: their features, use cases, and pros and cons.

1. Informatica PowerCenter

Pros

  • Mature enterprise-class solution.
  • Compatible with many different data sources.

Cons

  • High prices.
  • Challenging learning curve.

Informatica PowerCenter is an enterprise data integration platform that is commonly used for ETL (extract, transform, load) processes and constructing data warehouses. PowerCenter is part of the Informatica suite of enterprise cloud data management tools.

PowerCenter is well-known for its workload automation capabilities and its metadata-driven approach. What’s more, the platform can work with a vast array of data sources, including both SQL and NoSQL databases.

As one of the biggest players in the data integration field, Informatica PowerCenter charges steep prices to its customers, and may have a slightly higher learning curve than some of its competitors. Still, if you have large quantities of enterprise data to crunch, Informatica PowerCenter may be just the ticket you need.

2. Xplenty

Pros

  • Prebuilt integrations with more than 100 data sources.
  • Simple point-and-click interface.
  • Easy scalability.

Cons

  • Custom integrations may require more effort and knowledge.

Xplenty is a data integration platform that provides a complete toolkit for constructing data pipelines from source to target database. The tool’s point-and-click interface makes it easy for even non-technical users to get started integrating their enterprise data. Xplenty comes equipped with capabilities for more than 100 data stores and SaaS applications, including those on the public cloud, private cloud, and on-premise infrastructure.

For those who want a bit more control over the data integration process, Xplenty provides a rich expression language and an advanced API that enable developers to customize the software to their liking. What’s more, Xplenty’s elastic infrastructure makes it easy to scale your data integration processes up or down, depending on your exact business requirements.

3. Microsoft SSIS

Pros

  • Free enterprise-class tool built into Microsoft SQL Server.
  • Wide range of custom add-ons for additional functionality.

Cons

  • No direct support for push-down of joins.
  • Poor performance from Slowly Changing Dimension (SCD) wizard.

Microsoft SSIS (SQL Server Integration Services) is a feature of the Microsoft SQL Server database software that allows users to perform data integration as part of the ETL process. The SSIS tool is often overlooked since it comes “free” with Microsoft SQL Server, but it packs a mighty punch.

Developers can use pre-built SSIS templates to add their own customized components, or they can choose from the wide range of available add-ons that enable connections to Microsoft Dynamics CRM, Oracle, and many others.

Like many ETL tools, Microsoft SSIS has a couple noteworthy drawbacks: there is no direct support for push-down of joins, and the Slowly Changing Dimension (SCD) wizard has poor performance out of the box. Still, if you can work past these issues, Microsoft SSIS is definitely worth investigating.

4. Talend Open Studio

Pros

  • Part of the Eclipse software development ecosystem, which is familiar to Java developers.
  • Many different connectors for different types of databases.

Cons

  • As an open-source tool, may require more technical knowledge or upgrading to the paid version.

Talend Open Studio is a powerful open-source data integration platform for ETL processes that is built using the Eclipse RCP (Rich Client Platform), which means that developers who use the Eclipse IDE should feel right at home. For more advanced features, users can switch to Talend’s paid Data Management Platform, which offers features such as more connectors and management and monitoring capabilities.

Still, Talend Open Studio comes equipped with plenty of connectors that can link up with a variety of database types and extract the information inside. Users praise the tool’s predefined functionality, while cautioning that Java developers might be needed for more complex projects.

If you can put up with the quirks of open-source software and have some technical skill on staff, then Talend Open Studio might be enough for you. If you aren’t quite as savvy and need guaranteed technical support, however, it’s likely better to go for the paid version of the platform.

5. Panoply

Pros

  • Support for features beyond data integration, including schema modeling and query performance optimization.
  • Importing data is drastically simplified.

Cons

  • Only suitable for companies without on-premises data stores.
  • More complex ETL job flows may be challenging.

Panoply is a self-service data warehouse in the cloud that claims to drastically simplify the task of collecting and analyzing your information. Data integration is included as one of the features of Panoply, but the solution also supports other capabilities such as schema modeling, storage optimization, and query performance optimization.

On the software review website G2Crowd, Panoply has an average rating of 4.5 out of 5 stars. Users praise the platform’s ease of use and customer support. However, they also mention that troubleshooting issues can be difficult, and the platform may not be a good fit for more complex ETL job flows.

As a cloud service, Panoply is only a suitable solution for companies who have already migrated their data away from on-premises databases. If you’re already fully committed to the cloud, however, Panoply is worth the look.

6. Oracle Data Integrator

Pros

  • Good choice for existing Oracle customers and large enterprises.
  • Support for many different languages and technologies.

Cons

  • Uses the ELT process, not ETL.
  • May not be suitable for those not already using Oracle products.

Oracle Data Integrator (ODI) is a comprehensive data integration software product from Oracle. Naturally, the platform integrates easily with other Oracle solutions, so it’s a good choice for existing customers of Oracle software such as E-Business Suite and Hyperion Financial Management.

There are two things to point out on the technical side of Oracle Data Integrator. First, the software is set up to use the ELT (extract, load, transform) process rather than ELT, like the other tools discussed so far. Second, ODI is an on-premises solution, although it also has a cloud equivalent: Oracle Data Integration Platform Cloud.

Because it’s part of the Oracle software suite, ODI has fewer capabilities than some of the other tools on this list; these features are instead packaged into other Oracle applications. In addition, note that ODI is probably best suited for large enterprises, as is the case for most of Oracle’s software offerings.

7. IBM InfoSphere Information Server

Pros

  • Cost savings for existing IBM customers.
  • Powerful features for processing massive quantities of enterprise data.

Cons

  • Very steep learning curve.

IBM’s InfoSphere Information Server is an advanced data integration platform that includes massively parallel processing (MPP) features for crunching huge quantities of enterprise data.

G2Crowd users give InfoSphere Information Server an average rating of 4.0 out of 5 stars. Reviews say that InfoSphere Information Server is “good if you already have IBM licensing,” since you can save on costs and the software integrates well with other IBM tools (like ODI with Oracle).

Perhaps the most common complaint about InfoSphere Information Server, however, is that the software is difficult to use and confusing, with frequent updates and redundant functionality. One reviewer writes that “younger developers typically require several years of on-the-job training before they become proficient in using the product.” 

8. Qlik/Attunity

Pros

  • Part of the Qlik product suite for business intelligence and analytics.
  • Easy drag-and-drop interface.

Cons

  • Some users report a tricky learning curve.
  • Expert knowledge required for better performance and more complex integrations.

Qlik is an end-to-end platform for business intelligence and analytics. In February 2019, Qlik acquired Attunity, a provider of data integration and data management solutions, and incorporated its software as part of the Qlik product suite.

The Qlik data integration platform now consists of multiple applications: Attunity Replicate for data replication and ingestion; Attunity Compose for data warehouse automation; Attunity Enterprise Manager for overseeing your enterprise data pipelines; and Qlik Data Catalyst for data management.

One major benefit of using Qlik’s data integration offerings is the ease of compatibility with other Qlik software. For example, the Qlik Sense self-service analytics tool makes it simple for even non-technical users to navigate data and uncover key relationships and insights. Users can create interactive visualizations and dashboards with a straightforward drag-and-drop interface.

9. Denodo

Pros

  • Uses data virtualization to enhance the performance of the data integration process.
  • Support for both on-premise and cloud databases.

Cons

  • Smaller user community makes getting support more difficult.
  • Higher licensing costs.

Denodo calls itself the “leader in data virtualization,” providing integrations for information from enterprise sources, big data, and the cloud. Data virtualization is a technique that allows users to interact with a “virtual data layer” that behaves in a predictable manner, without having to duplicate the data and regardless of the data’s underlying representation.

Both legacy systems and cloud databases can be connected using Denodo’s healthy collection of APIs. According to reviews on the website of IT research firm Gartner, “connectivity with various sources is good and works well,” and the software “allows for quick and easy integrations with various data sources.”

Lightweight yet powerful, Denodo is an interesting choice for any company that wants to explore the new technology of data virtualization.

Conclusion

Enterprise data integration and management is tough to do right, as the sheer volume and variety of information continues to increase. However, you can stay ahead of the curve by picking the data integration tool that is most beneficial to help you achieve your objectives.

No matter what data integration tool you end up choosing, it needs to be the right fit for your business requirements. By taking the time to understand all your options, you’ll be more likely to use a high-quality solution that will stay with you now and into the future.

Interested in learning whether Xplenty is the right data integration tool for the job? Get in touch with our team of experts for a free trial of our data integration software. Learn why clients like Samsung, Gap, and IKEA all use Xplenty to extract more value from their enterprise data.