Introduction to Data Integration Tool
The following article provides an outline for Data Integration Tool. Data Integration is the process of bringing in data from various unidentical data sources to set it up to a single combined arrangement of data in a common format. It is carried out using specific tools, which can accomplish the complete set of Integration activities. Some commonly used tools available in the market for Data Integration are CloverDX, Linx, Informatica, Panoply, Microsoft SSIS, Snaplogic, Liaison, Infosphere, etc.
Top Tools for Data Integration
With many Data Integration tools available in the market, selecting the best tool for your project is quite a tedious task.
Hence here is a list of data integration tools you can select the best tool to meet your needs:
1. Skyvia
It is a cloud platform data integration tool mainly used for backup, integrating data from different sources, data warehouses, and databases, and managing and accessing cloud applications.
Features:
- Uses online query tools for managing cloud applications and databases.
- Provides automatic backup.
- Supports data integration scenarios like one-time migration, exporting and importing CSV, trigger actions, and loading and updating new data.
- Stores data relations.
- Support transformation like lookup, variance, constant, etc
2. Panoply
It is a data warehouse that automates the following key aspects data collection and transformation i. ETL, database storage management, query performance optimization.
Features:
- Connect to any business intelligence tools.
- With panoply, Query performance optimization becomes automated.
- It contains 100+ built-in automated sources of data integration.
3. QlikView
Another data integration tool is QlikView. It is used to create dashboards and applications automatically.
Features:
- As it supports GUI interfaces, interacting with data becomes easy by simply dragging and dropping.
- Provides security for data among all connected devices.
- Solves complex problems with simple solutions.
- Gives a quick response to any query or changes.
4. Syncsort
Syncsort contains a library of used cases like joins, weblogs, hash aggregation, etc. It is a popular data integration tool that has been used nowadays.
Features:
- Provides reliability.
- With Syncsort, scaling is possible.
- Increase the speed of response to the query.
- Reduces the cost structure.
- Without constraints, development can be done.
5. Alooma
It is a data integration platform used for business intelligence, analysis, and real-time data processing. It connects data to the cloud by performing extraction, loading, and transformation operations.
Features:
- With Alooma, it is possible to identify the interaction.
- Integrate data with zero latency, custom and native integration, and scalability.
- To analyze data from any database, it creates mashups.
6. Informatica
Another data integration tool is Informatica which connects to all data sources and retrieves data from those sources.
Features:
- Improves performance.
- It can combine with other software.
- The best design for developing code is offered by it.
- It has an error logging system that automatically identifies logging errors and stops them to prevent the data.
7. Liaison
It supports all types of integration methods. It supports data integration operations efficiently.
Features:
- Integrated with other third-party tools.
- Many organization uses Liaison To monitor data activities, loading status, etc.
- It helps to increase efficiency.
- Perform ETL, i.e., extraction; transformation loading can be done between any two applications.
- For cleaning data, it allows the user to use complex pre-post-processing rules.
8. HVR
This is a Data integration tool because of its distributed architecture; HVR can move data within an organization and cloud-based systems. It processes high data volumes with minimum impact on the performance of the database. Replication of data within RDBMS, data warehouses, data lakes, or the cloud, etc., is supported by it. It enables real-time analytics and fast deployment of use cases by providing a log-based CDC.
Features:
- It supports all real-time cloud data integration scenarios with a single configuration.
- In real-time, ensure data is updated.
- It is a Data movement accelerator.
9. Attunity
Attunity Connect is a data integration solution that is easy to use. It provides quick, easy, affordable access and availability of data. It provides replication, synchronization, distribution, consolidation, and data collection across warehouses, big data platforms, and different databases.
Features:
- The enterprise data source has a wide range of access.
- We are simplifying and expediting integration with the full VSAM, IMS / DB, and DB2 data software suite.
- Attunity has the mainframe integration industry.
10. Snaplogic
This is a useful integration tool as it helps IT departments, corporations, and other business lines to connect more quickly. It provides faster execution speed when using cloud apps such as Workday, Salesforce, and ServiceNow.
Features:
- One can easily and securely share data from one location to another location.
- Integration has been provided to big data sources like Hadoop and NoSQL Sources.
- Supports a wide range of SaaS, Enterprise, Big Data, Mainframe, and File connectors.
11. Dell-Boomi
The Boomi AtomSphere is a service platform for data integration (iPaaS). It offers a lot of powerful data management and integration capabilities.
Features:
- It provides integration to B2B data and applications.
- It is lightweight.
- Dynamic run-time engine.
- It provides automatic Integration updates.
- Complex integration automation.
12. Talend
This is an open-source data integration tool. Talend provides robust data integration software for companies.
Features:
- It provides a pipeline design for faster and smarter development of data integration work.
- Talend is considered the next-generation leader in cloud and big data integration software.
- Talend offers the ability to easily adapt to the latest news from big data and the cloud.
Conclusion
Data integration is a method of combining distinct information types from distinct sources. You can choose the desired data integration tool based on your requirements and by comparing the features mentioned in this article.
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