Data Integration Tools and their Types in 2022

Data Integration Tools and their Types in 2022

Introduction to Data Integration Tools

Data integration tools manage, combine selected systems, and understand the varieties of data derived from multiple sources in one single information system. The benefits of saving time, reducing issues, improvising collaboration, and delivering great results are obtained through such software.

There are multiple types of tools having their pros and cons which vary on the applicable cases and organization size. Keep thorough research and compare the big data integration tools before applying specific software in use.

In this article, let us keep a read on the list of the top 10 data integration tools in 2022.

What is Data Integration Tools?

Data integration tools are software designed to quickly connect business applications that carry out the process of combining and integrating data from multiple varieties of data in one single platform.

With the digital revolution, these tools are broadly in use for data analysis, mapping data, cleansing, business intelligence, identifying issues from pre-defined data and undefined coefficients, automate processes to help grow your business.

Data integration ingests, modifies, integrates, and provides structured data into a flexible data warehouse platform saving time to meet the data consumption requirements of business applications and end users.

The different types of data integration tools are,

1) Cloud-based Data Integration Tools

2) On-premise Data Integration Tools

3) Open-source Data Integration Tools

4) Proprietary Data Integration Tools

Lists of Top 10 Data Integration Tools 2022

What makes integrating data so important? Well, the numerous products contain varieties of data in-store. The tools combine large volumes of different data together, pick out the quality issues, and draw more accurate data.

This in turn ultimately improves the value of business data and saves good time which is a luxury for enterprises.

At times, it can be time-consuming to find the right statistical tools in research for your data integration needs. So, here’s an overview of a few of the top data integration tools that will elevate the business to the next standards, saving time and driving progress.



Hevo is a great data integration tool for those looking to replicate data in real-time from 150+ sources, 15+ destinations - SaaS apps, data warehouses, databases, and many more, to the choice of your destination.

Automate, scan workflow, identify issues, extract data within minutes, sync with pipeline platform, and supports ETL and ELT with zero data loss. Not only does it leverage data easily, but comprises 100+ Pre-built connectors across databases.


Data integration tools 1

Suggested Read: Data Processing - A Beginner's Guide


It is designed as a hybrid type of data integration service. It sequences SQL server integration services on Azure.

Works with multiple data connectors and offers compliance capabilities, enhances productivity which allows enterprises to integrate applications effortlessly. Microsoft Integration Technology offers productivity, connection, and security with ITL services on the cloud platform.


Data integration tools 2



It is a fully managed, no-code data integration platform that associates dashboard tools and cloud-based services, data warehouses, and data lakes.

This allows replicating warehouse data or moving data from the choice of your destination to improvise convenience and availability to the end users. Enable users to explore three products that are;

- Data to Dashboards

- Data Anywhere

- Headless Data Integration


Data integration tools 3

This tool is a no-code and low-code data warehouse integration suite for e-commerce that allows users to make decision making and get actionable data.

Integrate.i.o. modifies your data warehouse into a data platform that supports ETL, ELT, reverse ETL, and API management. Give an offer free trial period of 7 days.

Build connections with reputed e-Commerce providers like BigCommerce, Shopify, and Magento and are trusted by leading e-commerce brands - Nike, 7-Eleven, Grofers, and others.


Data integration tools 4


IRI Voracity

Is an on-demand data integration tool that cleanses and simplifies data analytics, and brings rapid ETL and analytic alternatives powered by proven IRI CoSort and Hadoop engines.

Voracity puts all the data together to locate, move, integrate, governance, and analytics in a controlled metadata framework set up on Eclipse™.

IRI provides multi-source data in the same I/O faster than SQL, legacy ETL, and BI tools. IRI speed data mastering solutions in a single data management medium consistent with COBOL, Erwin, Git, KNIME, MIMB, Splunk, and more.


Data integration tools 5



Presents advanced hybrid data integration ability with an Intelligent Data Management Cloud (IDMC) for data management.

It works with an integrated no-code development platform that speeds good data-driven growth.

Meanwhile, it enables companies to integrate cloud-based data that performs similarly to Software as a Service (SaaS).  Informatica PowerCenter aims to integrate, cleanse, and validate big data and other data management functions.


Data integration tools 6



It is another robust data integration tool to automate, innovate and accelerate data-driven decisions. This unique tool data merge for standardized and unstructured data.

Data from varying sources are organized in a consistent format that sticks to the enterprise standards in real time. The IBM features come with profiling, transformation, matching, and enrichment of data that helps to simplify workflows, data evolution, and analytics systems.


Data integration tools 7



ZigiOps is a no-code integration platform that creates compelling integrations and connects systems within minutes.

It allows users to integrate codeless, synchronize entities, scale, customize use cases, and automate data exchange with bi-directional integrations for your business applications data.

Zigiwave keeps up with 30+ connectors across ITSM, ITOM, Cloud, DevOps, and CRM platforms that adhere to changes in real-time data exchange.


Data integration tools 8



Oracle data integrator is another comprehensive cloud-based data integration platform. The features have Machine learning & AI capabilities to migrate, profile and govern that transform data faster into data warehouses.

The plan enables users to support connectors across all RDBMS, oracle, and non-oracle technologies.

Users connect to these data integration services they want to integrate and select which application they want to use to improvise their workflow.


Data integration tools 9



An iPaaS Data Integration tool that offers self-serve functionality to integrate, process, and assemble data for analytics. This enables users to easily collect, map, and categorize structured and unstructured data in a user-friendly interface at the cloud scale.

These data analysis tools automate processes and enterprise-grade data security including SSO with flexible scalability.

Celigo provides a low-code GUI-based flow builder that enables users to create custom integrations from the starting point.


Data integration tools 10



We have briefed some of the best data integration tools above but the list expands with instant marketing trends having their benefits.

To advance in this field, which is a high-paying profession in the corporate space, get a certification in Big Data Analytics Training Course.

With the increasing usage of the internet and data shared extensively, skills in data integration are even more demanding and challenging. Getting certified by a recognized training provider like Sprintzeal will help you achieve your career goals and chances for several job options.

Check out these big data training courses to boost your career:

CompTIA Data+ Certification Training

Big Data Hadoop Certification Training Course

Data Science Master Program


Frequently Asked Questions (FAQs)

What is a data integration tool?

Data integration tools are software-based tools that consolidate, transform, ingest, and transfer data from its original source to a choice of destination in one single information system.


What is the best data integration tool?

Some of the popular data integration tools used widely in the current market are as follows:

- Dell Boomi

- Hevo Data

- Informatica

- Jitterbit

- Keboola

- Pentaho

- SnapLogic

- Talend

- Zigiwave


What are the types of data integration?

A few of the types of data integration to keep in mind are;

- Application-based integration

- Common storage integration (sometimes referred to as data warehousing)

- Manual data integration

- Middleware data integration

- Uniform access integration


How many types of APIs are there?

Four. These types of web APIs consist of composite APIs, internal APIs, open APIs, and partner APIs.

Subscribe to our Newsletters

Blog Post

Nchumbeni Yanthan

Nchumbeni Yanthan

Nchumbeni is a content writer who creates easy-to-read educational blogs, articles, varying client request, and social media content helping millions of learners meet their career goals.

Trending Now

Big Data Uses Explained with Examples


Data Visualization-Benefits and Tools


what is Big Data – Types, Trends and Future explained


Data Science vs Data Analytics vs Big Data


Big Data Guide – Explaining all Aspects 2023 (Update)


Data Science Guide 2023


Data Science Interview Questions and Answers 2022 (UPDATED)


Power BI Interview Questions and Answers 2022 (UPDATED)


Data Analyst Interview Questions and Answers 2022


Apache Spark Interview Questions and Answers 2022


Top Hadoop Interview Questions and Answers 2023 (UPDATED)


Top DevOps Interview Questions and Answers 2022


Top Selenium Interview Questions and Answers 2022


Why Choose Data Science for Career


SAS Interview Questions and Answers in 2022


How to Become a Data Scientist - 2022 Guide


How to Become a Data Analyst


Big Data Project Ideas Guide 2022


What Is Data Encryption - Types, Algorithms, Techniques & Methods


How to Find the Length of List in Python?


Hadoop Framework Guide


What is Hadoop – Understanding the Framework, Modules, Ecosystem, and Uses


Big Data Certifications in 2023


Hadoop Architecture Guide 101


Data Collection Methods Explained


Data Collection Tools - Top List


Top 10 Big Data Analytics Tools 2022


Kafka vs Spark - Comparison Guide


Data Structures Interview Questions


Data Analysis guide


What is Data Integration? - A Beginner's Guide


Data Analysis Tools and Trends for 2023


A Brief Guide to Python data structures


What Is Splunk? A Brief Guide To Understanding Splunk For Beginners


Big Data Engineer Salary and Job Trends in 2023


What is Big Data Analytics? - A Beginner's Guide


Data Analyst vs Data Scientist - Key Differences


Top DBMS Interview Questions and Answers


Top Database Interview Questions and Answers


Trending Posts

Data Science Guide 2023

Data Science Guide 2023

Last updated on Dec 13 2022

Apache Spark Interview Questions and Answers 2022

Apache Spark Interview Questions and Answers 2022

Last updated on Aug 30 2022

Kafka vs Spark - Comparison Guide

Kafka vs Spark - Comparison Guide

Last updated on Jul 7 2022

Hadoop Architecture Guide 101

Hadoop Architecture Guide 101

Last updated on Apr 12 2023

Big Data Certifications in 2023

Big Data Certifications in 2023

Last updated on Apr 28 2023

Data Analysis guide

Data Analysis guide

Last updated on Aug 23 2022