Fivetran Reviews

Real-time streaming and SAP are the primary use cases of the solution.

The simplicity of the solution is its valuable feature.

The solution is very expensive. I would like to have a better integration of the solution with Azure.

I have been using the solution for one year.

It is a stable solution.

It is a scalable solution that is recommended for only enterprise companies because small and medium companies do not have the expertise and money to run Fivetran.

The technical support is good.

Previously, we used ADA tester and the solution is easy to implement with Azure Cloud. It is easier than Fivetran. Fivetran on the other hand is good for real time.

The solution is not easy to setup for a startup and SME but if an enterprise wants to do everything hands-on, it's okay for them. The deployment takes a couple of weeks to complete. Two people are needed for implementation.

The licensing costs are extremely high for the usage of somebody who has one GB or two GB of usage per day for real-time traffic. There are many other players in the market which are similarly priced or competitively priced. On average per month, it used to come around 12,000-15,000 USD, which is very high.

I rate the overall solution a seven out of ten.

We use FiveTran to do data integration and pipelines into data warehouses for analytics. We do the typical use case of bringing in from our internal systems, data syncing, change data capture, as well as bringing from third-party systems, like Salesforce, NetSuite, and even Google Analytics and web platforms. We use the solution primarily in an ELT framework. 

The main benefit is just being able to onboard new sources of data. One of the things that we did was create a staging database in FDLC. We set up a new connection, and a new source in destination. We're able to sync and set up a one hundred gigabyte database from PostgreSQL to Redshift, a completely new implementation that's subsequent to the initial one, within two days. We are able to completely replicate an entire staging environment within a two-day timeframe.

There's the general feature of the platform where it just makes it very easy to integrate different things, but I would say a specific difference is their integration of DBT, being able to have the transformation components be driven by Fivetran.

One of the traditional issues with the platform has been logging. The logging, while they have it, is not particularly verbose, so when there are issues it becomes hard to do. They also have internal logs versus customer-facing logs. We've asked FiveTran to provide more exposure on that or to be able to subscribe to it via an API or Datadog or something like that to pull from their system. 

Another thing is mainly their breadth of being able to pull from different systems. They have some of this already, but they're pushing to do some integrations with Excel online. Some of the pain points we're looking at are trying to integrate some of the items in the Microsoft stack, so SharePoint and Excel, and then some of the newer Azure services.

The solution is mostly stable. For the breadth and number of connections, it's okay. The thing sometimes with Fivetran is that they'll have random outages for some functions. I have had a couple of cases where there were some critical errors that have taken too long to fix. One issue was that stripe data was not sinking correctly, and it took over two months to get resolution on that. 

When the solution is working, it works well. When it breaks, it is very difficult to troubleshoot and fix because it becomes almost like you have an in-house ETL process that you have somebody outsourced trying to fix. Plus, they're trying to fix it for multiple customers at the same time, and sometimes that can be competing. 

I would say the solution is mostly stable 98% of the time, but the 2% that it isn't, there are usually critical issues.

The solution is very scalable. In terms of the breadth of connections and things like that, it's definitely there. In terms of volumes, they're not necessarily in charge of the platforms themselves. For instance, Fivetran doesn't control the speed of our databases, but as long as it's working in concert with customer systems, it can work well. I think there's just some work that needs to be done in terms of tuning those capabilities so that it remains consistently scalable. For instance, when we're doing syncing on PostgreSQL and things like that, there's certain features and flags that you can use to make the process faster, so there's some coordination there. Other than that, once it's set up, it's usually pretty good.

On a daily basis, we have four or five people using it in the business intelligence and analytics area. The SRE team uses it, and I think sometimes software engineering uses it if they want to ingest data from other systems. Also, our business intelligence engineers and the site reliability engineer, plus data engineers use it as well.

The solution does require maintenance right now. Sometimes there will be alerts that come up in the system if you have schema drift or something like that. Usually, the business intelligence engineers manage that.

We use the solution as our primary ingest for all the data into warehouse. We're looking to expand it. We're on Redshift, but we have another company that uses Azure and the SQL server and Synapse, so we're planning on expanding use there as well.

Earlier on, there were growing pains with the tech support. Early on, when we had to engage with tech support, it was usually for more critical issues, so to me, that's almost like a four out of ten. Especially if we had business breaking issues like a severity one, those probably didn't get as much attention as we needed them to get. 

It has gotten a little bit better. I've heard they've reorganized some of their processes and handoffs because they try to do twenty-four by seven, so they have handoffs to different regions and are trying to do better with them. I think it's improving, but I haven't had to use them recently. 

Step one was connecting to them, then opening up ports to our cloud, verifying connections, connecting to our different databases from source destinations, testing, and implementing. Obviously, with the initial onboarding there's also security and things like that. 

The initial deployment was fairly small, so it didn't take a particularly long time, maybe a week on and off, in terms of just working with the team and opening ports and connecting. We're on AWS, so some of it was on our side having to do IM rolls and whitelisting.

From a day-to-day perspective of onboarding new ones, it's really just pointing towards sources, then the destinations, and then just doing verifications. Day-to-day is pretty easy. 

Our deployment was handled in-house by two people. One is an SRE engineer and the other is an analytics BI.

There are two things, but they haven't been fully quantified. One is the time required for onboarding new data sources, and then two is that we don't have to stand up a data engineering department or function. I would say potentially Fivetran could replace at least one full-time engineer. As far as ROI, we could say maybe one FTE worth of time, though, obviously, there's the contract expense that goes with that.

We started off with just our credit card and we made payments. Now we're on a separate and negotiated contract.

The pricing generally can be very expensive and a little bit opaque, but they can be negotiated down because it is a SA solution. They've changed the pricing model. They do it by monthly rows now, I think. Also, their pricing practices, when we experienced them, were not very good. They would automatically renew a contract without negotiation, which is not good practice from a client perspective. I would say they're a little bit on the expensive side, and their contract process is not particularly good, but there is a lot of potential flexibility.

My advice is to be very clear about how many rows or the volume of data because that is the main driver of the cost. Then, be wary of the contract terms if it has an escalator per year. Also, obviously just catalog all the different sources and then, if there are sources that aren't available, see if they're on the roadmap or if they have the capability of doing custom connectors.

If I'm comparing it to other solutions in the market, I'd give this solution an eight out of ten. 

I think it does a very good job of being able to quickly stand up and connect to sources. It's even possible from a startup perspective. If you only have one person, you can connect three, four, five, or ten different systems and be up and running in a very short timeframe without having to do custom work. The stability is good, the pricing is okay, and the service is okay, and I think there is significant value in the product. There are more competitors coming about that might offer more customization, but I think that out of the box, Fivetran is probably the easiest to use.

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 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 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.

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.

For this project, we are using both Fivetran and HVR; however, HVR has a limited number of connections, with only around 30 sources, whereas Fivetran has around 200 source connections. Therefore, if we are unable to connect with HVR, we are connecting with Fivetran.

Fivetran is a SaaS solution, so it is always on a public cloud.

Fivetran is remarkably easy to use; I haven't encountered any other data integration tool that is as user-friendly.

Fivetran has a lot of connectors and can currently connect to more than 200 sources. However, occasionally we come across a source that Fivetran does not currently connect to. We can request them to make a connector, but this can take some time. In the meantime, if we want to read through that API or add a custom connection, we cannot do it on Fivetran itself. We must use AWS Lambda and integrate it with our Fivetran account, and this must be done through the public cloud. The number of connectors has room for improvement.

I would like Fivetran to implement additional resource monitoring and restriction policies. I don't want to spend more than 100 or 1000 credits per week or have restrictions based on data sources. If a data source suddenly produces a large amount of data, I could manually pause the credits, but it would be very helpful if I could set policies like this.

I have been using the solution for almost one and a half years.

The solution is stable and I have not encountered any issues.

Fivetran is a scalable product that operates on a pay-as-you-go model, so we must be mindful of the potential for building a connector to it. I have not encountered this issue personally, but I am aware of people in my organization whose clients have experienced similar problems due to its scalability. Currently, we are migrating around 1000 rows per week. If someone were to run a full day, we might migrate 10,000 rows, which could consume up to 5000 credits for Fivetran in a week. I am uncertain of the dollar value of these credits, but it was estimated that they would last two months, yet they were used up in a week. Additionally, Fivetran does not have a resource monitoring feature, so we can monitor how much it has charged us, but we cannot set a limit, such as $2,000, to stop the usage.

We have contacted the Fivetran team for HVR support since HVR is supported by Fivetran, and they have been very responsive.

The initial setup is the easiest of all the data integration solutions. We don't need to do much; I have only done it with Snowflake and Databricks. We just need to set up a target or destination or protocol destination, which is really easy. On the left side, we have all the information we need to provide to Fivetran. On the right side, they have step-by-step documentation or procedures on how to find this or how to do that, even for connecting to data sources. Fivetran always gives us step-by-step instructions on how to do this, and Fivetran usually has fewer than 15 steps.

The implementation was completed in-house.

I give the solution a nine out of ten.

Fivetran is the most user-friendly data integration tool I have encountered. I have not needed any assistance from the Fivetran team, nor do I know anyone who has.

If we have data coming from multiple sources that need to be connected, such as our CRM, Salesforce, ERP, and SAP systems, it would take a lot of time to write programs for each one. To save time and allow our data engineers to focus on more useful tasks, it is better to use Fivetran. However, we should be mindful of the cost, as Fivetran uses a pay-as-you-go model. It is best to connect with the Fivetran team rather than setting up the connection directly. They may offer free data migration for a source for up to two weeks, depending on our negotiations. This can be very useful for the initial sync and can save a lot of costs.

I primarily use Fivetran to reduce the operational cost time of data engineering.

Fivetran's most valuable feature is replication.

Fivetran would be improved by adding the ability to integrate the data from third-party APIs. Its logs could also be more informative, and its real-time streaming data processing speed could be faster.

Fivetran is reliable.

Fivetran's technical support is really good, and if you're on their enterprise plan, they usually respond within an hour and keep you continuously updated on progress. However, it can sometimes take a couple of days for the problem to be fixed.

Neutral

Fivetran is very expensive, and its database-driven pricing model is outdated.

I would rate Fivetran seven out of ten.