Connect to traditional data sources
Connecto to Big Data and NoSQL
Data model creation
Business rules and workflow
Testing and debugging
Integration with data quality tools
Integration with MDM tools
Likelihood to Recommend
Mostly Fivetran can be useful for working with risk reduction operations during agile data analysis processes. I.e., in the short term the heaviest data movement operations would be safe. If you need to create an automated infrastructure for the data, the ability to create data list transformations in SQL is useful for keeping the work integrable or with schema changes. For situations that require a lot of speed: setting up the Fivetran platform is very easy, as you only need to authenticate the sources of the data to start working, and this is excellent for covering fast storage operations.
- Easily connects to source data using delivered connectors
- Transforms data into standard models and schemas
- Has very good documentation to help quickly setup connectors
Engineer in Information TechnologyHealth, Wellness and Fitness Company, 51-200 employees
- More detailed logging
- More flexible choices for time range over which records are synced
- More options for masking and excluding sensitive data
Engineer in EngineeringLegal Services Company, 201-500 employees
Premium Consulting/Integration Services—
Entry-level set up fee?
$1 per credit
Fivetran Editions & Modules
- per credit
Additional Pricing Details—
Based on 1 answer
Based on 2 answers
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.
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.
Return on Investment
- Development cost have reduced for each connector
- The pay-per-use model is still not out their which requires lot of overhead cost