In this article, we will learn about the top 10 data integration tools and their key features. But before proceeding to the tools we must understand the concept of data integration and how to choose the right tool for your business.
Data integration is the process of unification of the data from multiple data sources. All types of industries can use data integration tools to leverage information. On the other hand, It also streamlines operations, improves customer service, and improves overall productivity.
Top 10 Data Integration Tools and their advantages.
What is Data Integration?
Data Integration combines the data from multiple data sources like data cubes, files, and databases into a single database. In addition, Data integration follows steps of procedures like the ingestion process, ETL mapping, and data transformation.
There are 2 main types of couplings to approach data integration. They are as follows.
- A data warehouse component acts as an information retrieval source in tight coupling.
- In other words, to perform a tight coupling data is combined with the help of the Extraction, Transformation, and Loading (ETL) process.
- In Loose Coupling, the data remains on the source database.
- It consists of an interface that accepts queries from the user. The tool then transforms this query according to the source database and sends the query to the database. After that, the interface displays the result to the user.
How does data integration help businesses?
Many organizations receive all the data they need, but the data is stored on multiple databases. For instance, for a typical Digital Marketing company use case, the data from web traffic, customer service applications, and CRM tools must be combined together for various needs.
Similarly, when an organization needs an analytical report, to create this report we have to log in to multiple accounts for data, visit multiple websites, and regroup data from various applications. On the other hand, if the data is unified with the help of data integration, then it becomes easy to create analytical reports from a single database. Here are some other benefits organizations can gain from data integration.
- Employees of every department need to access the company’s data for their projects. Similarly, employees from all departments also generate the data that the organizations need. Organizations can improve the collaboration and unification of their systems with the help of data integration.
- When an organization integrates all the data, it helps to reduce the time taken in analyzing the data. It also becomes easier for employees to gather the data for creating the application.
- The company data needs to be properly integrated. For instance, if an employee is manually gathering the data, the employee must be aware of every location and every account that might contain the data. Similarly, the employee must install all the software that is required for data integration. But with the help of a data integration tool that integrates data in real-time, it reduces errors that can generate by manual integration.
Common features of Data integration tools
Data integration tools simplify the integration process. However, to choose the right data integration tool you should look for the features provided by the tool. Here are some of the features of data integration tools.
- Plenty of connectors: Data integration tools have more pre-built connectors for various systems and applications. Therefore, it saves more valuable time.
- Open-source: Some open-source tools provide more flexibility and organization can customize them as per their needs.
- Portability: Modern companies are moving to hybrid clouds so if the data integration tools are built once then companies can run it from anywhere across the world.
- Easy to use: With the help of its simple GUI interface, it is possible for employees to learn the tool easily and can also visualize the company’s data pipelines more efficiently.
- Cloud compatibility: A single data integration tool can work with the same efficiency as a single or multi-cloud.
Top 10 Data integration tools
There are various data integration tools in the market. It is difficult to find the best tools for your business. Therefore, here are the top 10 data integration tools with their features.
Hevo Data is a zero code Data pipeline, the main function is that it can connect with more than 100 data sources to the data warehouse. Similarly, it has an integrated BI tool that visualizes the pipeline.
- It is a secure application that is built with a fault tolerance architecture. It handles the data in a secure manner and avoids data loss
- This application has a very simple and interactive user interface, employees with basic knowledge can also perform operations.
- Hevo has a live customer support system with their chat, email, and call process.
- It also has a live monitoring support system that helps the user to check the flow of the data.
Hevo data offers a 14-day free trial. The best use case of Hevo data is that organizations whose data sources are on the cloud can use Hevo data for data integration.
Dell Boomi is used for cloud-based data integration. This tool comes with an inbuilt component and has a visual designer. In addition, organizations can integrate applications effortlessly via the web. Dell Boomi supports organizations of all sizes.
- SMBs and large organizations can use Dell Boomi for integrating a number of applications.
- It is capable of managing the data of private, on-premise, and public clouds.
- With the help of a reporting system, organizations can manage the integration reports in a single unified place.
The best use case of Dell Boomi is that organization can manage the data through hybrid data clouds.
Informatica PowerCenter tool provides a variety of services like data masking, data replication, ETL, and other data management services. For instance, organizations with heterogeneous data sources can connect and fetch the data to perform data processing.
- This tool is a platform for data migration and data validation.
- Large businesses can use this tool for data integration.
- It also supports other data-related processes like data cleansing and other data management operations.
The best use case of this tool is the organization with legacy data sources that are available on-premise can use this tool for data integration.
Talend is an open-source software tool that supports ETL solutions. In addition, it includes features like data preparation, data and application integration, and big data.
- It is a popular open-source tool.
- Talend provides a variety of services for managing advanced data.
With the help of Hadoop and NoSQL database organizations can install on-premise and cloud data sources.
Pentaho integration tool provides ETL services that collect, clean, and stores the data in a uniform format. Therefore, it is one of the popular data integration tools.
- It is simple to understand and use.
- Similarly, Pentaho supports various use cases like data replication to a data warehouse.
Users can use the graphical interface without writing a single code.
SnapLogic is an (iPaaS) integration platform as a service that enables a faster data integration process for business. For instance, the browser-based interface is easy to use and it comes with more the 500 pre-configured connectors.
- The reporting tool provides charts and a graphical view of reports for the users.
- It has a very simple UI. If the users do not have any technical knowledge, they can still integrate the primary database with the secondary database.
- Above all, it automatically detects any error in the data integration process and sends a log report for the same.
The best use case of this tool is that the user does not require any technical knowledge for processing data integration.
Jitterbit is one of the modern data integration tools that support SaaS, cloud, and on-premise applications. In addition, Artificial intelligence offers language translation in real-time, and speech recognition features.
- With the help of Jitterbit users can integrate two apps with the help of the inbuilt tools and templates.
- To make the transformation easier the user can easily map the fields with the help of Automapper.
- In addition, It has a separate environment to test the integration process without affecting the ongoing integrations.
DevOps, CRM, and ITSM systems support the Zigiwave tool. In addition, it provides a zero-code interface that helps users to process the interactions with few clicks. It is a secure tool that protects the data when there is a downtime in the system.
- It is a secure integration tool.
- It can synchronize the data in real-time. Therefore, the user cannot see any lag in the data integration process.
- Users can customize this tool as per their needs. Therefore, it is flexible to use.
IRI Voracity supports iPaaS data integration that allows users to connect 2 software with inbuilt APIs and provide services like data masking and MDM integrations. Similarly, users can track the transfer of the data easily with the help of the GUI interface.
- It creates a detailed report of the integration process. Users can track errors and other activities.
- With the help of the BI tool, users can analyze the data in one place.
- With its simple GUI interface, users can normalize and transform the data easily.
MuleSoft Anypoint Platform
MuleSoft is an iPaaS Data integration tool that offers businesses to connect 2 cloud application data or 1 cloud application data and other on-premise data. Similarly, this tool can store the data in the cloud as well as on local data storage.
- This tool provides a mobile support system that allows users to monitor and manage tasks.
- This tool can integrate with IoT devices also.
- Complex integrations can be performed with the help of this tool.
It is critical for businesses to have complete access to each and every data from all the data sources. In other words, Data integration helps businesses succeed and improves unified systems. It also improves productivity and boosts efficiency. The organization must choose the right integration tool for their operation according to the importance of the data.