Fivetran Reviews and Ratings

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.

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.

Use Cases and Deployment Scope

Streamlined, fully managed ETL tool to bring data from our SaaS applications into a centralized Snowflake warehouse. It enables us to run analytics across the business.

Likelihood to Recommend

Fivetran is perfect for companies that want to quickly establish an ETL process to get more data for analytics. Particularly if you don't have in-house technical data engineering expertise. Fivetran abstracts away the complexity of writing code for ETL pipelines and the maintenance burden of keeping those pipelines running well.

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.

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.

Use Cases and Deployment Scope

We use it for the majority of our ETL to our data warehouse

Likelihood to Recommend

When you need a super quick and easy way to load data from a third-party source to a warehouse when a delay of up to an hour is an option, Fivetran is the way to go. It is shockingly easy and yet does support a fair amount of sophistication at a reasonable cost. It lacks automation and infrastructure as code abilities and internal transformations are limited, but it shines at batch extraction and handles schema changes for you very smoothly.

Use Cases and Deployment Scope

We use Fivetran at my organization to securely replicate data from our production databases to our data warehouses in Snowflake, syncing production data at regular intervals on a daily schedule. This allows us to efficiently move data without impacting our production systems and allows us to keep more historically complete records of the life of data that exists in our production databases.

Likelihood to Recommend

Fivetran is a good choice if you want to get started quickly with replicating production transactional database tables to Snowflake with minimal impact on production. Setup is fast and Fivetran provides a user-friendly interface that can be used to resync individual tables if necessary. It's a good solution for a mature database schema where certain tables hold a very large amount of data, which when replicated into a system like Snowflake allows users to execute queries against the dataset that would otherwise be very slow and not perform well directly against the production database.

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.

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.

Use Cases and Deployment Scope

Fivetran has lots of digital connectors available with them required in our organization to make business decisions. Our Data management is the main consumer of the product, which then widely gets consumed in the organization's analytical format to make strategies. We are data-driven digital marketers that rely on data to make decision. The sources are expanding and handling them individually makes them very challenging and that's where Fivetran helps us solve the problem.

Likelihood to Recommend

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

Use Cases and Deployment Scope

Fivetran is used by our reporting and analytics team to ingest data from multiple SaaS, Ad platform, and internal data sources. Fivetran supports our ELT approach using delivered connectors for most of our data sources.

Likelihood to Recommend

[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.

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.

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.