Fivetran Reviews

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.

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.

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.

I mainly use HVR Software for replication and migration.

HVR Software is an asynchronous replication solution. Its arrays are powerful enough to handle migrations even when the replication is happening in the background, without causing any trouble with the ongoing traffic.

HVR Software's most valuable features are that it's simple to use and allows us to use the command line to quickly complete the entire universal replicative setup.

In the next release, I'd like to see an automated version of HVR with a script that can be run on a management server where we can provide all the information within the script, or the script can prompt the user to enter the storage area and volume details so that with just a few clicks, the solution will be deployed automatically in the background.

I've been using HVR Software for fourteen months.

HVR Software is stable.

HVR Software is scalable.

HVR Software's technical support could be improved. Whenever we log a case, the response that we get from the support is a bit delayed.

Positive

The initial setup was straightforward because we had all the required documentation.

We used an in-house team.

I've heard that the license for HVR is a bit costly compared to its competitors, but since it's reliable and efficient, I think the customer shouldn't be bothered about the cost.

I would rate HVR Software as ten 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 mainly use Fivetran for ETL.

There's a very good layer that allows you to connect different data sources and establish a very good ETL workflow. You can manage all of your connectors individually, which gives you a very good ability to trace which one of your ETL processes is running and when. The solution also allows you to schedule each of those runs with different cadences, depending on which plan you are on. At the same time, for those runs, you have the ability to hash, unhash, or map any data that might be sensitive or personally identifiable, and that's pretty robust. It's a feature in the standard plan, so you don't need the enterprise plan for that. One very powerful and cool feature is how you can integrate the solution with other transformation tools, such as dbt, or run the transformations within Fivetran itself to create a transformation layer on top of your ETL layer. That allows you to manage the entire ETL workflow end to end from within the platform without the need for any additional tool.

When it comes to managing ETL pipelines, these features are valuable.

Given that Fivetran is a fully managed third-party solution, the customization could improve because Fivetran gives more thought to people who don't want to manage analytics workflows rather than engineers who want to be able to customize pipelines more thoroughly.

I've had experience with Fivetran for about two-and-a-half to three years.

The scalability will directly relate to the plan you're on. It will be very important to see that the provisioning in compute and the provisioning you have to run workflows and jobs will also be directly related to your use case. Managing scalability in that way is a bit complex, but you get a lot of support from Fivetran.

From a customer support standpoint, Fivetran does an amazing job in establishing and helping you customize while ensuring you have the right plan for your data needs. I have full contact with our account executive, and she's super nice and walks us through many of these use cases that will be important in the future and many of the estimations we might need for the workflow we plan on integrating.

Positive

I have used Splunk before, and it's more technical. Splunk allows you to version things and have a good engineering process around your ETL pipeline. It also has very good logging and documentation tools. But now that Fivetran has a better exposed API, it is much more flexible. But Splunk beats Fivetran regarding things like customization, for example. We switched to Fivetran because we reduced the engineering team. We had fewer people to manage all the different ETL processes, so we had to leverage more automated third-party tools, and Fivetran made onboarding new engineers a lot easier.

Fivetran is very easy to set up. It's a matter of having the connection information of each one of the endpoints you want the ETL through. The solution is very comprehensive and easy to set up. It even gives you assistance on where to find the information that you might need, depending on the data source. It has pre-built connectors for the most common data sources, so it also helps you expedite that process if you are not super tech-savvy.

Fivetran has a pricing model that scales the more data sources you add. When you have a lot of workflows and complex use cases, pricing goes down as you use it more. That's a very good feature of its pricing. Fivetran might be a bit pricey for a very limited or small number of data sources that might be easily collected in other forms. The pricing gets better the bigger you are.

Comparing Fivetran to other tools such as dbt, AWS Glue, or Azure Data Factory, the other tools are more robust and allow us to run custom transformations.

To anyone who uses the product, I say monitor. You have a dashboard to monitor your MAR, which is a row-level metric Fivetran uses to gauge how much you are consuming. If you can monitor your MAR closely, you can get a very good understanding of how much data you're moving, and it will allow you to adjust the cadences you might need to get a better bang for your buck. Watch your numbers and try to plug in as many data sources as you need because that will help you with pricing.

I rate Fivetran a seven or a seven-point five out of ten. It's solid and offers a very simple UI and way to get set up. It might fall short for people who want more advanced use cases or people who have knowledge and tools that they can integrate, and that's where things get a bit more technical. But I feel the leap from just getting started with it to getting very technical with it is very large. There's no middle ground.

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.