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Great tool for data transfers
What do you like best about the product?
Fivetran is easy to use and setup for someone who's not VERY familiar with coding. It's very easy to use and setup daily transfers (you can choose the frequency) for our Databases across multiple tools.
What do you dislike about the product?
The column names don't fully match the original source. There's an undescore added.
What problems is the product solving and how is that benefiting you?
Getting access to data bases in 1 data lake system. We can now merge data across systems in GCP.
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Tons of new useful information...especially the new Hybrid Data Lake
What do you like best about the product?
No code required and the automatic schema updates
What do you dislike about the product?
The cost is a little high for our organization
What problems is the product solving and how is that benefiting you?
As we migration to the cloud having a data integration tool like Fivetran speeds up this migration
Amazing Company
What do you like best about the product?
They care about the future and seem to have a grip on things that other competitors dont.
What do you dislike about the product?
They are great but are on the costly side. it is something to think about when starting your data journey
What problems is the product solving and how is that benefiting you?
We need to sync data from many sources over to our data warehouse and they seem to do the trick for us
Reliable platform, little pricing transparency
What do you like best about the product?
Most of the older connectors are reliable -- consistent data, a consistent data delivery schedule, easy setup, implementation, and integration.
What do you dislike about the product?
We operate Fivetran in a multi-tenant environment. While not all Fivetran users will have a similar setup, this creates numerous problems.
1. Schema standardization. If we connect the same source for different customers, often different table schemas will be delivered to our destination. Columns will appear in one instance but not another. Column datatypes will be different between instances. Tables may be missing entirely. This problem required us to write a series of very complicated custom scripts to standardize the data delivery.
2. Pricing transparency. Fivetran is very opaque about pricing. Daily summaries of row usage by table are provided, but we often incur large charges where Fivetran is unable to explain why those charges were incurred. The lack of pricing auditability is a big issue.
3. Standard tables. This is a new feature that Fivetran began rolling out mid-2024 which will drastically run up our Fivetran costs if we aren't watching carefully. They are turning on dozens of "standard reports" for common connectors that may increase our usage (and costs) by 5-10x. Currently these cannot be programitcally disabled with the Fivetran REST API.
4. Data delivery control. While we can control database and schema names from Fivetran, we cannot change the behavior of 1 Destination to 1 Database and 1 connector to 1 schema. This has shoehorned us into an unsustainable architecture as we grow.
5. Customer support is below average. If an issue moderate to hard they will close your ticket and not address it.
1. Schema standardization. If we connect the same source for different customers, often different table schemas will be delivered to our destination. Columns will appear in one instance but not another. Column datatypes will be different between instances. Tables may be missing entirely. This problem required us to write a series of very complicated custom scripts to standardize the data delivery.
2. Pricing transparency. Fivetran is very opaque about pricing. Daily summaries of row usage by table are provided, but we often incur large charges where Fivetran is unable to explain why those charges were incurred. The lack of pricing auditability is a big issue.
3. Standard tables. This is a new feature that Fivetran began rolling out mid-2024 which will drastically run up our Fivetran costs if we aren't watching carefully. They are turning on dozens of "standard reports" for common connectors that may increase our usage (and costs) by 5-10x. Currently these cannot be programitcally disabled with the Fivetran REST API.
4. Data delivery control. While we can control database and schema names from Fivetran, we cannot change the behavior of 1 Destination to 1 Database and 1 connector to 1 schema. This has shoehorned us into an unsustainable architecture as we grow.
5. Customer support is below average. If an issue moderate to hard they will close your ticket and not address it.
What problems is the product solving and how is that benefiting you?
Fivetran gives us quick access to data from common APIs.
Reliable Data Integration with Fivetran
What do you like best about the product?
Our team saved a lot of time using Fivetran. We were able accelerate adoption because of its user-friendly interface and step by step guidelines to set up connectors. We were able to connect 30+ data sources and not have to worry about schema drifts and other data engineering tasks. Also, we used Fivetran’s sdk to build custom connectors for complex integration. Customer support helped us a lot when we encountered issues. They would reply within 12 hours and offer detail feedback which helped us resolve issues quickly.
What do you dislike about the product?
The main concern we have with Fivetran is the pricing model. It can increase rapidly as they volume of the data increases and also the compute costs will increase when the sync frequency increases. Fivetran gives a 2-week free trial to estimate costs before you turn on the connector, but it is hard to get an additional budget mid fiscal year. Also, you will need to use Fivetran with another tool like dbt to handle complex transformations.
What problems is the product solving and how is that benefiting you?
Fivetran solved the challenge of replicating data from various sources to our Snowflake Data Warehouse. Before using Fivetran my team would have to spend a lot of time maintaining custom data ingestions or using other ETL tools that were not optimized for data ingestion.
Great Managed Solution with Room for Improvement
What do you like best about the product?
Fivetran's ease of use is definitely its standout feature. The platform is simple to navigate and doesn't require much manual intervention, which is great for streamlining data workflows. I also love the variety of connectors available—most of the tools I need are supported, and it's clear that Fivetran is continuously expanding its offerings. The managed aspect of the service means I don't have to worry about maintenance, and that’s a huge plus for saving time and resources.
What do you dislike about the product?
The pricing can be a bit of a pain point, especially as data usage scales up. While the managed service is convenient, the cost feels like it could be more aligned with varying business sizes or budgets. Additionally, some connectors are missing certain features or options that would be helpful, and having more customization or advanced controls would improve the overall experience.
What problems is the product solving and how is that benefiting you?
Fivetran solves the challenge of maintaining reliable, automated data pipelines without requiring constant monitoring or manual intervention. By managing the entire ETL (Extract, Transform, Load) process, it allows my team to focus on data analysis rather than spending time on data integration. It streamlines data flow from multiple sources into our data warehouse, ensuring that we always have up-to-date data for reporting and decision-making. This has significantly reduced the time and effort spent on managing integrations and troubleshooting, ultimately improving our operational efficiency.
A really easy out of the box tool
What do you like best about the product?
The best thing about Fivetran is how easy it is to set up and to get going.
What do you dislike about the product?
Fivetran costs are quite high, especially with third party tools where you can't control the format of the data.
What problems is the product solving and how is that benefiting you?
Initially, Fivetran was useful to replicate internal data when we didn't have access to engineering resources.
Now we primarily use Fivetran to ingest data from external tools
Now we primarily use Fivetran to ingest data from external tools
Easy setup
What do you like best about the product?
Simple, 600+ drivers for data ingestion, easy integration of workflows
What do you dislike about the product?
Sometimes, customer support takes time to follow up
What problems is the product solving and how is that benefiting you?
Ingestion made easier
Fivetran Review
What do you like best about the product?
Ease of use and number of connectors available for different sources
What do you dislike about the product?
Their line connector feature requests are not so useful
Support could be so much more better and No slack integration for alerts
Support could be so much more better and No slack integration for alerts
What problems is the product solving and how is that benefiting you?
Fivetran is solving us the problem of having to manage a Data Engineer and solves us the need to manage separate self hosted pipeline to extract data from multiple sources.
The Best Ingestion Tool
What do you like best about the product?
Users can set up and manage data pipelines with minimal technical expertise.
Fivetran supports near real-time data syncing, which is crucial for making timely decisions based on the most current data.
It can handle large volumes of data and scale as your data needs grow. This scalability ensures that performance remains consistent even as data complexity and volume increase.
Fivetran supports near real-time data syncing, which is crucial for making timely decisions based on the most current data.
It can handle large volumes of data and scale as your data needs grow. This scalability ensures that performance remains consistent even as data complexity and volume increase.
What do you dislike about the product?
Relying on Fivetran means depending on a third-party service for critical data workflows. If there are outages or issues on their end, it could impact your data integration processes.
What problems is the product solving and how is that benefiting you?
It automates the data extraction, transformation, and loading (ETL) process. T
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