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Fivetran Information Reviews & Insights

Score8.4 out of 10

52 Reviews and Ratings

Community insights

TrustRadius Insights for Fivetran are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Intuitive Accessibility Permissions: Users have found the accessibility permissions within Fivetran to be intuitive, allowing them to easily secure and identify the allowed managers for data administration. This feature has been praised by multiple reviewers.

High Scalability of Data Replication Operations: The high scalability of data replication operations in Fivetran has received praise from users. It is ideal for creating backups of information in both cloud and non-cloud environments, ensuring source systems are well-protected. Several reviewers have highlighted this advantage.

Quick and Effective Customer Support: The customer support representative provided quick solutions to fix issues with the platform, as acknowledged by a user. Despite the issues being configuration errors on their part, the positive experience with Fivetran's support team was appreciated.

Fivetran Reviews

4 Reviews
InformationComputer Software3Internet1

Automating the data extraction and loading part with ease

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

We want to load data from various operational systems into our central data warehouse. Fivetran supports this task with minimal setup and maintenance effort on our side. This allows us to focus on the value adding tasks instead of on moving data between systems. We use Fivetran to sync data from CRM, Marketing Automation, ERP, HR, Subscription Management and Billing, and Support systems.

Pros

  • Small initial setup effort
  • Fivetran automatically takes care to fix loading issues
  • Has connectors to many different systems

Cons

  • Very difficult to get connectors enhanced if a specific needed object is not supported by them
  • Depending on the edition needed and the data volumes, can get quite expensive

Likelihood to Recommend

If your source systems have a supported connector and the provided schemas from Fivetran work for you, then I consider it well suited. Also make sure based on your volume estimations if the costs work out for you. If you want to focus your data engineers on more value adding tasks and outsource the "moving data from A to B" part, then Fivetran is a great match. If you want to custom-develop all the data integrations and have a sufficiently large workforce to do so, then you might not need it.
Vetted Review
Fivetran
4 years of experience

Fivetran - next generation data replication

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

Fivetran is used as a near real-time data replication solution between several source systems and organization-wide databases. Sources include traditional RDBMS, APIs, SAP Hana, etc. Fivetran is a reliable, and available service that did not result in any performance or data issues during its tenure with the data platform. It also supports some data transformations which are helpful to some use cases.

Pros

  • Near real time Data replication
  • Basic standardization
  • Availability of a wide variety of ingestion plugins

Cons

  • View based ingestion from RDBMS
  • Detailed Logging
  • API support

Likelihood to Recommend

Fivetran is very well suited for any near real-time ingestion requirements for available plugins. Do not use it for complex data standardization as it only supports some features with that respect. Fivetran provides the required information on data volume, cost applicable, which is helpful to plan future ingestions. Sometimes historical refresh cost goes very high, but users also can be trained to save cost with appropriate measures.

Highly recommend Fivetran

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

We use Fivetran as our Extract Transform Load provider bringing data from all our various third-party services into our Data Warehouse in Microsoft Azure. Personally, I've used it extensively with Twilio's SendGrid connector in bringing and formatting all of our email and notification data into the warehouse for data analysts internally to run more extensive analysis on it.

Pros

  • UI is very clean.
  • Documentation is easy to use.
  • Plenty of connectors for different third party services.

Cons

  • Honestly, not much they're already crushing it!
  • If I had to say one thing, I guess I would say make it more accessible to non-data engineers.

Likelihood to Recommend

I think it's suited best for what it was built for, ETL pipelines expedited. If you are a startup that has a software product with various different data sources that you need to quickly and reliably bring all together to some kind of centralized data store, Givetrain is well suited for this use case. If that isn't part of your business needs to do this data consolidation before any analysis it probably isn't well suited for your use case.
Vetted Review
Fivetran
1 year of experience

Gets data from Point A to Point B

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

We use it to sync a MySQL instance to a redshift cluster so we can run analytics against a non-prod environment.

Pros

  • Quick replication of data with minimal lag.
  • Automated reporting if data is out of date.
  • The customer support team is relatively good.

Cons

  • A full schema refresh takes us two-three days and knocks us offline from monitoring up-to-date business KPIs, running updated analyses, etc. This is likely due to us having massive amounts of data (from a count(1) perspective, not size of tables perspective).
  • There's little to no progress estimate on the front end UI to see how long this refresh might take and you need to enable back end logging in Amazon to see where it's at in the sync process and derive rough estimates of completion time.

Likelihood to Recommend

Fivetran works well when you have a lot of data in different places and want to get it all in one spot. I don't think it's as necessary if you have one cluster that needs to be replicated against and the data could wait a day. In this instance, there are other tools.