Fivetran vs. gathr.ai

[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

1. For ingesting multiple data sources to multiple data emitters. 2. Creating ETL pipelines in easier manner. 3. Easier to collaborate with multiple products. 4. No manual efforts, as it provides drag and drop feature for creating and maintaining data pipelines. 5. Easy to play with structured and unstructured data and schemas.

• 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

• 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

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

The interface is intuitive, and the prebuilt connectors eliminate a lot of complexity

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

• 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