Fivetran Reviews

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.

This solution was previously called HVR, which stands for "high-volume replicator." It is now part of Fivetran. It is useful when you need to migrate a large volume of data. We use it for massive data migrations from 30 or 40 sources, including the file system database and some transitional systems. 

In our case, we had historical and active data. Everything was in on-premise Oracle databases. The historical data itself was around 4.5 terabytes. Fivetran is currently deployed in an AWS EC2 instance.

Fivetran can perform data migration incredibly fast, depending on the source and target. 

The documentation is decent, but it's hard to find information online about Fivetran. For example, if you try to search for an error code, you won't find much information about it in forums. 

The CI/CD capabilities aren't user-friendly. It's easy for simple tasks, but sometimes I get error codes that aren't well-defined in the system or the documentation. 

We also experience some lag when migrating between two database sources. Data transformation is expensive, so it's segregated across multiple accounts. It would be helpful if we could unify those into a single transformation component or integrate the solution with other transformation tools. It was built for data replication, not transformation. 

We have been using Fivetran for the last five or six months. 

I rate Fivetran nine out of 10. The only problems we've faced were due to network issues, but there were some bugs in the previous version. 

Fivetran can handle large amounts of data. 

I rate Fivetran support nine out of 10. They've been excellent so far. Some of my team is in the United States because our organization has partnered with Fivetran. They respond quickly when we raise a ticket. I have no complaints. 

It comes down to cost and volume. I don't think other tools are as cost-effective as Azure if we're dealing with vast amounts of data. However, Fivetran or other tools make more sense if we're dealing with less data because they're easier to use. We did POCs for Matillion and Fivetran. Migrating more than 4 or 5 terabytes of data from on-prem to Snowflake cloud would have cost a lot.

I wasn't involved with setting up Fivetran, but I'm told it was straightforward. You have to set up a hub and then install it. If you have an on-prem database, it's better to install an agent. That will help with encryption, data transfer, compression, and other things. You can do it without an agent, but the agent will help. We have agents installed on all our data sources. Updates are also easy. We only need to stop the instance while installing the newest version and restart it. 

We started an annual subscription for HVR, and Fivetran acquired it in March last year. They have the same pricing model based on monthly active rows of data migrated. 

I rate Fivetran eight out of 10. I would recommend Fivetran depending on the volume of data. If you only need to migrate a few gigabytes, it might be too costly for you. It's better to go with other tools in those cases. 

If you need to work with large volumes of data, go with HVR or Fivetran. It's easy to set up, but getting a trial version is difficult. You need to talk to Fivetran support for a demo. There isn't a free version on their website that you can install. If you contact Fivetran or a Snowflake partner, you can get a two-week trial.

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 are ingesting data from various SaaS tools.

The general data ingestion is valuable. It's used for a lot of data. It provides about 90% of the data we use in our data warehouse without needing data engineering.

Fivetran is very expensive for data sources with a lot of rows, such as email data. I would like to see cheaper pricing for data sources like that.

I have been using this solution for three years.

Some connectors are more stable than others. It seems it depends on which API they're connecting to.

It's scalable. We have six users who are using this solution. In terms of our plans to increase its usage, if we start using additional SaaS tools, we will add them to Fivetran.

I would rate them a four out of five.

Positive

We didn't use any other solution previously.

It was straightforward.

It was implemented in-house. It requires less than one person for deployment and maintenance.

We have seen an ROI.

I can't give exact amounts because that's based on usage, but it's more expensive than some of its competitors.

We evaluated other options.

It's excellent for any eCommerce data and advertising data, but consider another solution for the data that uses a lot of rows.

I would rate it an eight 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 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.

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 this solution for integration with different data sources to push data to our data warehouse, BigQuery and regularly updating the data.

We have four people using this solution in our business. 

Making the decision to implement Fivetran was supported by the fact that they have better connectors than other competitors. 

There was a random change to our contract in a unilateral manner after the first year. The overall cost of using Fivetran was then unclear and this is the reason I would not recommend this solution. 

One of the main selling points during the first implementation was the ability to carry over credits from one year to the next. This option was later removed and impacted their credibility as a service provider. 

I have used this solution for two years. 

This is a stable solution. 

I would rate the technical support for this solution a nine out of ten. 

Fivetrans has specific connectors that provides information we need for our processors and the other companies didn't have them at that point in time. 

The initial setup was not that simple because our database sources had a very old configuration, which in some cases could not be changed.

Our ROI using this solution is limited due to the high cost of the solution. 

In the first year, we were given a very good discount. It was approximately 20,000 Euros per year. In the third year, we purchased credit for two years and the price was 33,000 Euros per year.

I would advise others to get a contract for five years to begin with. I would rate this solution a five out of ten. I would rate the product and technical support a nine out of ten but there are other solutions on the market that offer similar performance and are more reliable.