Fivetran Reviews

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Fivetran is very expensive, and its database-driven pricing model is outdated.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

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.

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.

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. 

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.

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.

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 primarily use the solution for business intelligence.

We use it for data publishing, data logs, and data refreshes These services are all very good.

The interface needs to be more user-friendly.

Data security should be improved in the next release.

The solution is stable. We've never faced any stability issues.

The way we are using it, I think the solution's level of scalability is sufficient for us. We didn't really need anything bigger. For us, it's been fine so far. We have about 30-40 users. There's no need for us to increase usage at this point.

We've never really used technical support, so I can't speak to the level of quality.

The initial setup was complex. We had quite a few data sources, so the database replication was quite in-depth and we had quite a few environments that needed to be refreshed. 

Right now, we have a corporate license. I'm not sure of the term of the license or the cost.

We use the on-premises deployment model.

I would rate the solution eight out of ten.