Hevo Data vs. Talend Data Integration

It is of great help for unstructured data sources. The way Hevo Data flattens the high nested data is amazing. Schema management is also good by Hevo Data. The way it's tell about the data type and then we can identify any error in the model. Additionally, It is very easy to setup for any new user and once model is created then we do not have to worry about the script maintenance and updating the script daily.

Incentivized

The same way you design data integration job can be used to design services. It is easy to enhance by custom components and can adapt to all requirements. Talend Data Integration connects to [a] multitude of data sources and streaming service. Very easy interface to design complex applications without spending much time on coding. Easy to learn and master. Talend constantly strives to better itself by adding more features and functionalities.

• Hevo is the best tool when you want to manage a large number of pipelines. With Hevo you can automate the pipelines very easily.
• Hevo's great features are automatic detection and notification of failed data pipelines.
• Auto mapping feature is also good. It's makes really easy to move the data.
• Integration is easy with so many databases like SQL, Google Sheet, etc.

Incentivized

• We used Talend to ETLing the data from myriad sources such Oracle Database, Clarify, Salesforce, Sugar CRM, SQL DB, MQ, Stibo Step, FTP, Netezza, and Files.
• We leverage Talend transformation capabilities for stitching the data , unions and join
• We successfully created the final unified set that can be used by business

Incentivized

• Transformation
• More Sources
• More Destinations

Incentivized

• Pricing for sure can be the area for improvement.
• Real time processing is slow as compared to other tools like Abinitio.
• While developing batches, it crashes a lot. It may be the issue with me, but I wanted to highlight it.

Incentivized

We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.

Incentivized

Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution

Incentivized

Much lower cost and faster syncs but not as good support. More flexible in terms of pricing, though. Fivetran requires annual contracts and is very inflexible.

Incentivized

In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, while Talend is more classic. It has both on-prem and cloud approaches, while Matillion is only cloud-based.

Incentivized

• Comprehensive results from the data processing is a perfect approach from the tool.
• Authentic data models brings a high automation process and more productivity.
• Expansive data sourcing brings clarity and genuine results after inferential analytics.

Incentivized

• It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations.
• 40K+ plots data, covering 1K+ crop varieties.
• 3K+ Customer & their credit data, 3K+ product inventory & pricing.

Incentivized