Google Cloud Dataflow vs. Hevo Data

It is best in cases where you have batch as well as streaming data. Also in some cases where you have batch data right now and in future you will get streaming data. In those cases Dataflow is very good. Also in cases where most of your infra is on GCP. It might not be good when you already are on AWS or Azure. And also you want in-depth control over security and management. Then you can directly use Apache beam over Dataflow.

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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.

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• Streaming, Real time work load
• Batch processing
• Auto scaling
• flexible pricing

• Extract
• Load
• Transform
• Support

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• More templates for Bigquery and App Engine. There is only limited options for templates so the things we use can limit.
• I would like native connectors for Excel (XLSX) to reduce the need for custom wrappers in financial pipelines.
• Debugging Google Cloud Dataflow using only logs in Cloud Logging can be overwhelming sometimes, and it’s not always obvious which specific element in the flow caused a failure. IT uses a lot of time.

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• Support - their support teams try to be helpful, but often miss the mark
• Error logging - we've run into a few issues debugging errors and limited support is provided by Hevo

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It really saved a lot of time and it's flexibility really can give you infra which is future-proof for most of the use cases may it be streaming or batch data. And with this you can avoid use of resource-heavy big data offerings.

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Google Cloud Dataproc Cloud Datafusion

1. Cost efficient 2. Creation of automated pipeline 3. Can load data from multiple data sources 4. Updates data in near real-time - We were able to get near real time insights from the data model which we have created in hevo 5. It has good integration with different BI tools

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• cost saving from managing our own data center for ETL servers
• consumption based pricing
• with auto scaling feature, we were able to expand components to support work load

• 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.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info