In my current project, the specific use case of Fivetran is bridging the gap between siloed data, allowing me to extract and have it in the same data warehouse. Fivetran works with its seamless connections to sources and destinations, helping to avoid reinventing extraction logic from scratch. Fivetran already has data models, so it pulls in data quickly, providing it all in the same data warehouse.
Fivetran Data Movement Platform
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Has accelerated data integration workflows and supports seamless development of custom connectors
What is our primary use case?
What is most valuable?
I've worked extensively with Fivetran, mainly used for extraction purposes, and I've worked with the transformation element in it as well. Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner. I don't have to write raw Python scripts or dumping scripts; it offers straightforward examples and guidelines, making it much simpler to develop custom connectors inside Fivetran. We've been able to develop many custom connectors as well, which is unique and beneficial for having everything centralized instead of having those connectors located elsewhere.
One of the best features by Fivetran is its clean, simple, and intuitive UI. It includes a transformation section where I can deploy my DBT queries and scripts. It also supplies good tracking capabilities for billing estimates and user permissions, allowing for customization to the desired level. The number of connectors it has remains a standout feature, and within connectors, the options available are very helpful. Although it sometimes appears static due to its built-in nature, it offers good flexibility for data transformation and caching, which I appreciate because it saves us extensive script-writing time.
What needs improvement?
The experience of using SDK connectors can be improved, as it lacks computational power, which is an area that needs enhancement. Additionally, for some connections, I want more flexibility during ingestion, specifically for transformations needed beforehand. When we tried to use a built-in Oracle connector, it didn't allow for the tweaks we needed, which led us to the SDK connector route and caused delays in development.
For how long have I used the solution?
I've been working for almost four years in this field, and it has been a really great learning and challenging opportunity, allowing me to work on various different stacks and to learn and grow extensively.
What do I think about the stability of the solution?
In my experience, Fivetran is stable with very few instances of downtime or reliability issues, and overall, I am very happy with it.
What do I think about the scalability of the solution?
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs. However, the performance with SDK connectors could be improved, as it took around 10 to 12 days to conduct historic ingestion for just two years, which I find unsatisfactory.
How are customer service and support?
Customer support from Fivetran is quite good; it's really nice and responsive. I am very happy with my experiences in reaching out to them.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Before Fivetran, we used Skyvia, which is a no-code ETL tool. I also considered Data Factory as an alternative. However, I found Skyvia lacking in maturity and Data Factory better suited for enterprise solutions but limited in connectors. Scripting solutions demanded more work and included additional costs, which led to my decision to switch to Fivetran.
How was the initial setup?
My experience with pricing, setup costs, and licensing has been satisfactory; however, I notice that as row numbers increase significantly, it can get a bit more expensive. Overall, it's fairly reasonable.
What about the implementation team?
We see fewer employees needed due to Fivetran's efficiency, which translates to money saved, as employee wages are much higher compared to the costs associated with the software itself.
What was our ROI?
Fivetran provides time savings, cost reductions, and improvements in data quality. For example, in working with Shopify, we faced numerous errors and challenges with in-house complicated connectors. The time directly correlates to cost; when the time investment decreases, fewer developers are needed, which means significant savings. Generally, we have seen very few instances of data quality issues since implementing Fivetran.
Which other solutions did I evaluate?
Before selecting Fivetran, I evaluated other options including Stitch, Rivery, Hevo, and Skyvia among others.
What other advice do I have?
My advice for those looking to use Fivetran is to rely on its documentation, which is very straightforward and accurate. Avoid depending too much on AI for Fivetran issues; the dedicated documentation suffices for most inquiries. If problems arise, Fivetran's support team is quick to assist. I rate Fivetran 9 out of 10.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Fivetran data connectors helps in my daily work to pull data from different source and updates data
What do you like best about the product?
They are easy to use
It makes data implementation and integration easier
Maintenance of the data is easier
Saves time and efforts
They are multiple pre-built connectors
there is a community for the customer support
It makes data implementation and integration easier
Maintenance of the data is easier
Saves time and efforts
They are multiple pre-built connectors
there is a community for the customer support
What do you dislike about the product?
It maybe costly for the startup companies and small business.
The software delays due to frequency of use of huge amount of datas
Syncing of data fails on large data`s
The software delays due to frequency of use of huge amount of datas
Syncing of data fails on large data`s
What problems is the product solving and how is that benefiting you?
Fivetran makes moving and syncing data super easy. It handles updates and changes automatically, saves engineers time, and works well with custom connectors and dbt. Costs can go up with lots of data, but overall it’s a reliable, hassle-free solution
A great automated tool for data integration
What do you like best about the product?
1. Its ability to move data between different platform
2. It is easy to connect to different sources like API's,databases etc,
3. The data integration and movement is very easy.
4. It also acts as ETL tool.
2. It is easy to connect to different sources like API's,databases etc,
3. The data integration and movement is very easy.
4. It also acts as ETL tool.
What do you dislike about the product?
1. Pricing is bit high compared to other connectors.
What problems is the product solving and how is that benefiting you?
1. I used this mainly for data movement using fivetran connectors to my databases. I use the raw data further and make the analysis.
Seamless data integration with fast setup and responsive support
What do you like best about the product?
Fivetran makes data integration incredibly easy. Setting up connectors takes only minutes, and the automated pipelines handle schema changes seamlessly. The sync process is fast and reliable, and the documentation and UI make it straightforward to monitor jobs. Whenever I had questions, the support team was responsive and helpful, making adoption smooth.
What do you dislike about the product?
There’s not much to dislike given the overall value. Pricing can be higher than some alternatives, especially for smaller data volumes, but the ease of setup, speed, and excellent support make it worthwhile.
What problems is the product solving and how is that benefiting you?
Fivetran eliminates the need to build and maintain custom data pipelines. It automatically replicates data from numerous sources into our data warehouse, which allows our analysts to focus on generating insights instead of managing integrations. The platform keeps pace with schema changes and ensures data is synced quickly and accurately, saving us significant engineering time and enabling more timely reporting.
Reliable Data Sync with a Pricey Tag
What do you like best about the product?
I appreciate Fivetran's ease of setup and usage, which made integrating our systems straightforward. Its reliability and secure platform ensure smooth data synchronization across multiple databases. I value its robust networking capabilities and the helpful services it provides for SaaS applications. Additionally, it simplifies schema management with its flexible features and supports enhanced data delivery and performance.
What do you dislike about the product?
I find Fivetran's pricing to be quite expensive. If the cost could be reduced or there were more flexible pricing options available, it would be more accessible to a larger group of users.
What problems is the product solving and how is that benefiting you?
I use Fivetran to sync data across multiple databases effortlessly with a reliable and secure platform. It simplifies ETL processes, supports easy schema changes, and offers fast data delivery, enhancing my data management experience.
Basic use of the product for data analysis
What do you like best about the product?
I like the end to end automation the most.
What do you dislike about the product?
The price, the cost of the product is a bit expensive.
What problems is the product solving and how is that benefiting you?
The automation of data analysis upload/download so that there is minimal work for the user.
Real-time data replication and integration streamline processes and enhance productivity
What is our primary use case?
The usual use cases for Fivetran that I work with involve real-time replication from Oracle Fusion, Oracle DB, and some of the APIs. I also work with replication from S3.
What is most valuable?
The most valuable feature of Fivetran so far is the data replication. The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline. Even when an error occurs, it automatically tries to solve the issue without manual interaction needed.
The effectiveness of Fivetran's pre-built connectors in enhancing my customer's productivity is significant because everything is easily configurable. The documentation is very clear, so there's no difficulty in finding the necessary steps. Everything is pre-documented. The pre-built connectors that are available are excellent. Most functionalities are covered, and in most cases, it works according to expectations.
What needs improvement?
If Fivetran can build in more transformations, that would be really helpful in my opinion.
For how long have I used the solution?
I have been using Fivetran collectively based on project requirements. I work with AWS, GCP, Snowflake, and Fivetran as part of my experience. My experience with Fivetran specifically extends to about two to three years, depending on project requirements.
What was my experience with deployment of the solution?
I have not experienced any challenges with deployment.
What do I think about the stability of the solution?
From my experience, Fivetran is very reliable. They have 99.9% accuracy on the data load and they maintain transparency. When the data is loaded, they clear it from their storage, keeping only metadata for MAR calculation and pricing purposes.
How are customer service and support?
I often communicate with the technical support of Fivetran whenever we encounter issues. I would rate them a seven. If they could provide support more quickly, that would be great.
How would you rate customer service and support?
Positive
How was the initial setup?
I usually participate in the initial setup and deployment of Fivetran. I handle the solutioning from start to end.
What other advice do I have?
I don't use Fivetran's automated ETL feature, but after loading, we use dbt for the transformation.
I have not used Fivetran's Schema Drift Management feature.
The integration with data warehouses such as Snowflake and BigQuery has been successful. Fivetran has clear documentation on configuration for both warehouses.
Regarding pricing, Fivetran uses MAR pricing, which I would consider moderate. The pricing consideration ultimately depends on the project budget since the client is responsible for payment while I implement the solution.
On a scale of 1-10, I rate Fivetran a 9.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Google
Great set-it-and-forget-it solution for ELT workloads
What do you like best about the product?
Huge connector library and "it just works".
What do you dislike about the product?
You have to be careful about how many rows you are loading, given the Monthly Active Rows pricing model, which can get expensive quickly for large data sources.
What problems is the product solving and how is that benefiting you?
Allowing me to load my data sources into the warehouse so I can focus on building data models from raw data, rather than on building pipelines that load raw data. Allows me to skip having to build the extract and load step of ELT myself.
Good for large datasets - limited in terms of controls
What do you like best about the product?
It does effectively pull large data sets.
Integrations with various platforms
Integrations with various platforms
What do you dislike about the product?
Inability to schedule pulls, has to be every 24h. (Not necessarily for weekly / monthly reports so it seems excessive).
For CM360 it is difficult to pull 'Seat' or 'Network' as a dimension.
For CM360 it is difficult to pull 'Seat' or 'Network' as a dimension.
What problems is the product solving and how is that benefiting you?
It supports me in reporting in bulk - ultimately extracting large datasets and improving efficiency by saving time
Fivetran is Awesome.
What do you like best about the product?
Fivetran is super easy to setup and use. Mostly set and forget especially for known / existing connectors.
What do you dislike about the product?
Some connector doesn't fail as elegantly such as showing existing credentials that isn't working.
What problems is the product solving and how is that benefiting you?
I do not need a dedicated data engineer to babysit the processes because we have FiveTran.
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