AWS Database Migration Service vs. Fivetran

As stated previously, AWS Database Migration Service excels when replicating very specific data elements between environments. AWS Database Migration Service handles replication tasks to load equipment assets or customer job sites from production to QA databases very well. Full load replication - e.g., we need an exact copy of the production database in another region - works well. But when we need to load the QA database with the latest production data - it does work as well. AWS Database Migration Service comes up short because we do not want to wipe the QA database completely and make an exact copy. We want to keep what's already in the QA database and add production data so that we can QA with that level of volume. And at least with our database design, we end up having to do a lot of manual data manipulation and de-duplication.

Incentivized

[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

• 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

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

• Set it and forget it for maintaining data consistency - moderate cost, zero to minimal maintenance
• High touch production data loads into QA - negative ROI engineering time investment far exceeded our predictions

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