Fivetran Reviews

We are doing a proof of concept, and we are still building the operating model. We are using it for moving data from one source to another. We will be using HVR with Snowflake.

It is not like a traditional ETL, but it gives quite a lot of flexibility. 

It should have a few more monitoring functionalities. It should also support integration with more data sources. Currently, it supports Snowflake, AWS, and Google Cloud, but it can also support SAP integration. They can make it more flexible.

I have been using this solution for around six months.

It seems to be stable, but we have not yet used it in production. It is still in development. 

We are a large enterprise, but it also seems suitable for small and medium enterprises.

We have not contacted their support.

We did not do any deployment at all. We started around six months back, and we are just in the early stages of doing a proof of concept. 

We didn't evaluate other options.

Based on our experience so far, I would rate it an eight out of ten. We will get to know more about how it is in a couple of months.

We have multiple data available from multiple sources. We use the tool to collect the data in one data warehouse.

The product has some seamless connectors, which are readily available.

The connectors from some websites are not available. It is hard to get the data and work on it. The product should expose the APIs in a better way. The cloud functions are very code-centric. A low-code tool or a no-code tool would give us more flexibility. The environment must be more development-friendly.

I have been using the solution for two to three months.

The tool’s stability is good.

Five people use the solution in our organization. We need two people to maintain the tool.

The technical support must be improved. There are a lot of communication barriers. We raise a ticket and wait for days. The team has integrations with communication channels, like Slack, but we have to wait for the support team to look up the issue and answer. The team was proactive during the proof of concept, but the support got slower as soon as we got the license.

Neutral

The product is cloud-based. The deployment process is very straightforward. We get the data from different websites and integrate it into our database. We just sync the data on a daily or weekly basis. We needed two people for the deployment. It took two to three days to deploy the tool.

The solution is affordable. The pricing model is good.

We evaluated Domo, Snowflake, and Airbyte. We chose Fivetran because it was a prominent product in the market.

I did the proof of concept, and my organization is in the process of deploying the solution. We have a lot of issues. People who want to work with the product must list the requirements of the extraction website and the web sources from which the data needs to be extracted. They should choose Fivetran only if the connector is readily available. They must not search for custom connectors. Overall, I rate the tool a seven out of ten.

We use the solution to replicate data from our ERP.

The product is very easy to use and very easy to configure. We can do an end-to-end configuration in a few minutes.

The connections with SAP must be improved. The environment has some limitations.

I have been using the solution since January 2023.

The product’s stability is very good.

The tool’s scalability is very good.

The initial setup is very easy. It is not that complex. I was part of the deployment process. It is still ongoing. We are not running production for now.

We need two or three IT employees to maintain the solution.

The solution has good pricing. I rate the pricing a six out of ten.

It's a good integration tool. It is easy to use. Overall, I rate the solution a nine out of ten.

We use Fivetran to build data engineering pipelines. It helps us do a lot of data transformation and data extraction. 

Fivetran helps us save time and be more efficient because we do things with no-code/low-code. 

The most important feature of the solution is its ability to build data pipelines in less time. 

We experience cost issues because Fivetran is charged on a usage basis. When you reach a certain level, the tool should focus on reducing the costs. The solution is expensive when you are moving gigabytes and petabytes of data. 

It should also focus more on REST APIs and webhooks. 

I have been using the solution for two years. 

The solution is very stable and reliable. 

The product's scalability is high. 

Fivetran's technical support is average and can take weeks to respond. 

Fivetran's deployment is simple. 

I rate the solution a  seven out of ten. 

We use Fivetran for bidirectional data synchronizations between systems.

I didn't set up any transformation in Fivetran. I wanted Fivetran to take care of the log sequence number comparison between source and destination systems so that it would pick up only the data that needed to be synchronized, and it did it beautifully.

The most valuable feature of Fivetran is that it only synchronizes what needs to be synchronized. You need to capture the in-source updates and digits from the source; this is the only information you want. You don't want to download the whole thing each time. Fivetran does this just beautifully.

Fivetran should add more connectors because its competitors, like Airbyte, have more connectors. All of these systems have a problem, namely that they are pure cloud player solutions. I often work in hybrid solutions where customers have on-prem things mixed with cloud things.

Pure cloud player solutions never provide a good solution for what is on-prem, which leads to a gap. When you look at systems such as ActiveBatch, they have a very, very strong on-prem platform. They are also looking at the web and cloud things, but they are not that good at the cloud things. So there is nothing that is equally good for both on-prem and cloud.

Fivetran should add a feature to connect to the SQL server on-prem.

I have been using Fivetran for a month.

Fivetran is a very stable solution. After you set it up, you can forget about it. I rate Fivetran a nine out of ten for stability.

Fivetran saved me a lot of work. I could have hired a bunch of engineers to write Python's code for me, but Fivetran was already built. So, it was easier for me to focus on my line of business and purchase a commercial product without trying to replicate this myself in Python. That's not a return on investment; that is savings.

I am using the latest version of Fivetran.

Fivetran is easy to set up. It took me one or two hours to set up my flow, and then I forgot about it. So for me, it's perfect because it doesn't take a lot of time. It's not like some other solutions where you need two weeks of engineering to get them to work.

I would advise users to try Fivetran before they commit to it.

When I compare Fivetran with Airbyte, I like Airbyte better than Fivetran.

Overall, I rate Fivetran an eight out of ten.

I'm responsible for replicating the data from one source to another. It is constantly running, and we do nothing other than looking at monitoring reports. Once it is established, it is pretty much hands-off.

We are not using its latest version. We are slow to migrate to the new version. We wait until there is a need to upgrade, and we are generally one or two versions behind.

It has improved the way our organization functions.

The compare feature is the most valuable piece of it.

The documentation can be laid out better to make it easier to find things, and I really wish there was built-in support for changing passwords.

Some features don't work as advertised for the platform/repository database, and HVR is not always the fastest at getting results.

I have been using this solution for three years.

We like its stability.

We like its scalability.

They are adequate.

I have used GoldenGate replication previously.

Installing the software is really straightforward. Getting your replication stream working is a little bit more complicated, but it is not overly complicated.

Its deployment was done in-house. It took weeks. 

There are two people to manage it and make sure that it is working. They are part of the data team or the infrastructure team making sure that we're building our analytic pipeline.

I don't have the exact information, but I know it is high, and it is on a yearly basis. There is no additional cost for what we're doing.

We're always open to doing things cheaper, so we might potentially implement a different solution.

We looked at Informatica, but one of the sources that we had was only supported with HVR. That's why we went with HVR.

I would rate HVR an eight out of ten.

Fivetran is an ingestion tool used to move data between different sources and destinations. It helps orchestrate pipelines that can be set up manually without technical experience. It facilitates daily pipeline runs based on a specific schedule determined by the licensing level.

Fivetran has significantly reduced data ingestion lead times by about sixty to eighty percent. It requires less maintenance on pipelines, freeing up development hours by approximately twenty percent. Additionally, the platform allows for faster setup of new connections, reducing lead time from four to eight weeks to one or a week and a half for complex integrations.

The simplicity and scalability stand out as the most valuable features of Fivetran. It is easy for users to get accustomed to the tool due to its gentle learning curve and clear error transparency. The platform offers transparent logging for detailed auditing. Moreover, scalability is emphasized as Fivetran charges less per row as you use the service more.

Fivetran could improve in the area of customization, especially in how they socialize their tools. The feature of being able to deploy Fivetran on-premises for enhanced security should be highlighted more during discussions with executives.

I have used Fivetran for about four years now.

I rate the stability of Fivetran as nine out of ten. We have never experienced downtime issues.

I rate the scalability of Fivetran as nine out of ten. It offers a flexible cost structure that benefits those who use it more extensively.

Customer service is thorough but could be faster, rated as seven out of ten. They usually take about three to five business days to respond.

Neutral

Previously, everything was developed by hand using Python before moving to Fivetran. Fivetran was a significant improvement.

The standard cloud licenses are very easy to set up. However, more complex deployments like self-hosted can be more technical.

I managed the setup alone. In all the last two companies I've worked at, it has been a solo effort.

Fivetran has drastically improved our operations. We've reduced lead times for data ingestion by sixty to eighty percent and have fewer maintenance requirements, leading to a twenty percent increase in development hours. The system has simplified manual integration processes, leading to quicker setup times for new connections.

The pricing is sensible and depends on the data ingestion quotas. The standard enterprise allows for advanced development, while the free tier offers a limited feature set. High security options require a business-critical license.

We evaluated Airbyte, Snowflake, and Databricks before choosing Fivetran. Snowflake and Databricks were less competitive due to their complexity and higher resource costs.

Fivetran is a great tool for organizations needing to simplify data management and ingestion processes. It's ideal for those without a large team to handle multiple data tools.

I'd rate the solution eight out of ten.

Fivetran is used as an ingestion tool to move data between different sources and destinations. It orchestrates a series of pipelines that can be easily set up manually without any technical experience. These pipelines can run daily according to a specific schedule, depending on the licensing level. Fivetran addresses schema changes and updates destination tables unless there's a major difference, which is helpful in integrating systems from third parties.

Before using Fivetran, most integrations were done manually, leading to a lead time of four to eight weeks for a new connection. Now, I can set up new connections in anywhere from a day to a week and a half, reducing data ingestion lead times by sixty to eighty percent. 

There is a lot less maintenance to do on the pipelines, which has freed up development hours by about twenty percent. Overall, there's a big gain in development hours and less time maintaining data.

The simplicity and scalability are the strongest features of Fivetran. The learning curve is not steep, making it easy to get accustomed to. It's transparent in understanding when something fails, and the logging is detailed, which helps in auditing and accessing information rapidly. 

For scalability, Fivetran charges less per row the more you use it, allowing you to move more data economically as you set up additional data pipelines.

The biggest area for improvement is in customization, particularly in how Fivetran socializes its tools. Many features like deploying Fivetran on-premises for security purposes or using connectors specific to systems like SAP are not well communicated. New users might not be aware of these features due to the lack of socialization when there are new releases or updates.

I have been using the solution for about four years.

I would rate the stability a nine out of ten. I have never had an issue with downtime at all, though I have encountered technical issues using the API in a more advanced fashion for custom setups.

I rate the scalability as a solid nine. All you have to do is plug in a new data source, which contributes to your quota for different plans. Fivetran also provides flexibility in managing data ingestion costs through different plans.

The customer service is very good and thorough, however, it can be slow, usually taking about three to five business days for a response. Generally, I would rate it a seven out of ten because of this lead time.

Neutral

Before Fivetran, everything was developed by hand using Python. This switch to Fivetran was a big improvement.

The initial setup for the standard cloud licenses is straightforward and simple. It's a matter of connecting data sources to destinations, which Fivetran's platform largely automates once you input the correct information.

I handled the initial deployment myself.

Fivetran has drastically reduced the lead time for setting up new connections to one day to one and a half weeks, down from four to eight weeks. It has also decreased the time required for pipeline maintenance, resulting in a gain of sixty to seventy percent more development hours.

The pricing is based on how much data is ingested, not on the number of rows. The tool's features expand with higher licensing tiers, such as enterprise or business critical, which provide more secure options. The pricing is reasonable, allowing small companies to operate at a cost below forty thousand a year while larger companies experience diminishing costs per data unit as usage increases, projected not to exceed one hundred thousand per month.

We evaluated Airbyte, Snowflake, and Databricks. Fivetran was ultimately chosen due to its simplicity in setup and configuration. 

Snowflake and Databricks set up pipelines in a more complex way, and Databricks' orchestration workflow incurred heavier monthly costs.

Fivetran is a very good tool for simplifying data management and ingestion. It is particularly useful for tracing data lineage, ensuring data flows correctly, and is beneficial if managing multiple data tools requires minimizing complexity.

I'd rate the solution eight out of ten.