Fivetran vs. Google Cloud Dataflow

[Fivetran is] very well suited when you are using popular and common data sources, such as the major ad platforms, and SaaS platforms such as Salesforce. If the majority of your data sources are custom internal applications or databases, may be less value as you aren't leveraging the delivered connectors.

Incentivized

Based on my experience, streaming / real time / machine learning / AI type of processing and batch processing which needs less transformation are very well suited. Work load that needs complex transformation / multiple hops gets very complicated to implement. New feature like Dataflow SQL option will come in handy for sql heavy users.

• Simplified ETL from a wide range of data sources
• Stable and painless data pipeline
• Granular control over what parts of the data source are loaded

Incentivized

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

• Doesn't include support for a Kinesis stream as a data source so couldn't be used for some use cases under consideration
• Doesn't support the use of "BEFORE DELETE" triggers
• No support for serverless Aurora

Incentivized

• inbuild template options can be expanded
• more data connector options
• easy of use

Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

Fivetran came well with the connectors' availability and updates with the source changes. We had an idea on data requirements in our case which helped us to work out on cost implication and take a decision for Fivetran as a data provider for our organization. These were 2 places where Fivetran out-performed, other vendors.

Incentivized

Google Cloud Dataproc Cloud Datafusion

• Saved a lot of manual development days (unable to quantify)
• Accelerated the time to add a new source to the data warehouse a lot

Incentivized

• 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