Top 8 Cloud Data Integration

AWS GlueMule Anypoint PlatformInformatica Cloud Data IntegrationPalantir FoundryDenodoAWS Database Migration ServiceSnapLogicEqualum
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    We have found it beneficial when moving data from one source to another.The solution helps organizations gain flexibility in defining the structure of the data.
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    The most valuable feature is their integrations and very good API management.It can scale.
  3. Buyer's Guide
    Cloud Data Integration
    January 2023
    Find out what your peers are saying about Amazon, MuleSoft, Informatica and others in Cloud Data Integration. Updated: January 2023.
    670,331 professionals have used our research since 2012.
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    The serverless capability and the packaging application of the solution are valuable.Data integration is the most valuable feature. The ability to connect to any of the sources and enterprise applications makes our lives easier.
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    The data lineage is great. Great features available in one tool.
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    Denodo is lightweight in terms of how it leads you to combine your discrete data systems at one spot. The most valuable features are query optimization and the single language independence from the sources we're using to catch data.
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    Support is helpful.Even if it does break down, it will automatically recover itself and resumes from where it stopped.
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    Use our free recommendation engine to learn which Cloud Data Integration solutions are best for your needs.
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  9. The solution could improve its API management. The solutions ability to connect "snaps" or components to the graphic user interface is very intuitive, prevents errors, and makes implementations easy.
  10. I found two features in Equalum that I consider the most valuable. One is that Equalum is a no-code tool. You can do your activities on its graphical interface, which doesn't require complex knowledge of extracting, changing, or loading data. Another feature of Equalum that I like the most is that it monitors the data transfers and tells you if there's any issue so that you can quickly check and correct it. Equalum also tells you where the problem lies, for example, if it's a hardware or communication issue.

Advice From The Community

Read answers to top Cloud Data Integration questions. 670,331 professionals have gotten help from our community of experts.
Netanya Carmi - PeerSpot reviewer
Netanya Carmi
Content Manager at PeerSpot (formerly IT Central Station)
Dec 15 2022

What will companies benefit from if they select this type of data integration?

Netanya Carmi - PeerSpot reviewer
Netanya Carmi
Content Manager at PeerSpot (formerly IT Central Station)
Dec 15 2022

What capacities should a tool have in order to be effective for cloud data integration?

Netanya Carmi - PeerSpot reviewer
Netanya Carmi
Content Manager at PeerSpot (formerly IT Central Station)
Dec 15 2022

Which method is better in your opinion and why?

Cloud Data Integration Topics

What are cloud data integration tools?

Cloud data integration tools utilize cloud computing to allow companies to integrate data from various sources, manage it, connect with it, as well as access it on demand. These tools integrate the acquired data in a way that is accurate, complete, and up to date. Such solutions can be part of data integration platforms that combine a variety of tools. They may include:

  • ETL tools: Extract, transform, and load (ETL) tools facilitate one of the most common data integration methods.

  • Data ingestion tools: These tools allow users to obtain and import data for immediate use, as well as to store it for later use.

  • Data governance tools: These tools ensure various capabilities of data, including its security, usability, availability, and integrity.

  • Data cleansing tools: With this type of cloud data integration tool, users can replace, modify, or delete data in order to clean it up.

  • Data migration tools: These tools allow organizations to move data between computers, storage systems, and application formats.

  • Data catalogs: These tools give access to data assets scattered through multiple data silos and allow companies to find and inventory them.

  • Data connectors: Through these tools, data can be moved from one database to another as well as transformed.

  • Master data management tools: These tools assist companies in their adherence to common data definitions and the achievement of single sources of truth.
What challenges can cloud data integration face?

Cloud data integration is a relatively new concept, in comparison to traditional methods in this field. This is why users who want to utilize it can face several challenges. This field is fast-developing, and cloud data integration tools and platforms work to eliminate the possible drawbacks of the process. However, some of the challenges that the process may face include:

  • Unsuccessful data movement: Data integration is a complex process when it comes to data movement, and moving data between clouds gets even more challenging. Depending on the data volume and required frequency, as well as whether it is being moved between clouds or between cloud and on-premises systems, the process may require an extensive amount of time or introduce various errors. Cloud data integration requires detailed strategies in order to move data effectively in a set time frame.

  • Lack of standardization: As already stated, cloud data integration is a relatively new approach compared to some that are more established. This is why there is no standard way to integrate data from cloud to cloud or from cloud to on-premises systems. Although different tools and platforms have similar approaches, most of them vary in format and schema. The fact that cloud services are frequently upgraded and modified may create further difficulties for users, as they need to adjust to constantly-changing conditions.

  • ETL-related issues: ETL workflows serve to clean data and transform it into the format required by the target system. The challenge that cloud data integration may face with ETL is that many cloud systems work with unstructured data or provide flexible structured data models. While this can be of advantage to users, it can complicate ETL-related processes. In order to clean, treat, and convert data, cloud integration systems need to determine a method that does not over-complexify the processes or slow them down.

  • Architectural issues: Scalability is one of the main priorities of cloud systems, and some of them put data integration in second place. This is why, when rapidly scaling, it may be challenging to synchronize data with external systems.
Advantages of Cloud Data Integration

Cloud data integration provides organizations with various benefits, in comparison with traditional integration approaches. Some of the greatest advantages of this process include:

  • Cloud data integration improves operational efficiency for users.

  • The process is much more flexible and scalable than other approaches.

  • It offers companies faster time-to-market through easier access to their data.

  • Cloud data integration improves internal communication, as it can appoint role-based access to specialists and facilitate collaboration.

  • This innovative approach can increase the competitive edge of companies through cloud-based solutions.

  • Cloud data integration can automate workflows and modernize organizational processes related to manual data copying or entry.

  • Through this approach, companies can eliminate redundant data, as it can be gathered in one place, potentially reducing storage costs.
Buyer's Guide
Cloud Data Integration
January 2023
Find out what your peers are saying about Amazon, MuleSoft, Informatica and others in Cloud Data Integration. Updated: January 2023.
670,331 professionals have used our research since 2012.