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Fivetran vs Skyvia comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 1, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Fivetran
Ranking in Data Integration
13th
Ranking in Cloud Data Integration
9th
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
29
Ranking in other categories
Data Replication (3rd)
Skyvia
Ranking in Data Integration
57th
Ranking in Cloud Data Integration
26th
Average Rating
9.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2026, in the Cloud Data Integration category, the mindshare of Fivetran is 4.1%, down from 5.6% compared to the previous year. The mindshare of Skyvia is 1.5%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Fivetran4.1%
Skyvia1.5%
Other94.4%
Cloud Data Integration
 

Featured Reviews

Hafiz Usman - PeerSpot reviewer
Team Lead Data Engineer at Data Pilot
Has accelerated data integration workflows and supports seamless development of custom connectors
I've worked extensively with Fivetran, mainly used for extraction purposes, and I've worked with the transformation element in it as well. Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner. I don't have to write raw Python scripts or dumping scripts; it offers straightforward examples and guidelines, making it much simpler to develop custom connectors inside Fivetran. We've been able to develop many custom connectors as well, which is unique and beneficial for having everything centralized instead of having those connectors located elsewhere. One of the best features by Fivetran is its clean, simple, and intuitive UI. It includes a transformation section where I can deploy my DBT queries and scripts. It also supplies good tracking capabilities for billing estimates and user permissions, allowing for customization to the desired level. The number of connectors it has remains a standout feature, and within connectors, the options available are very helpful. Although it sometimes appears static due to its built-in nature, it offers good flexibility for data transformation and caching, which I appreciate because it saves us extensive script-writing time.
RH
CTO & Developer at a consultancy with self employed
The product works, is simple to use, and is reliable.
Error handling. This has caused me many problems in the past. When an error occurs, the event on the connection that is called does not seem to behave as documented. If I attempt a retry or opt not to display an error dialog, it does it anyway. In all fairness, I have never reported this. I think it is more important that a unique error code is passed to the error event that identifies a uniform type of error that occurred, such as ecDisconnect, eoInvalidField. It is very hard to find what any of the error codes currently passed actually mean. A list would be great for each database engine. Trying to catch an exception without displaying the UniDAC error message is impossible, no matter how you modify the parameters in the OnError of the TUniConnection object. I have already implemented the following things myself. They are suggestions rather than specific requests. Copy Datasets: This contains an abundance of redundant options. I think that a facility to copy one dataset to another in a single call would be handy. Redundancy: I am currently working on this. I have extended the TUniConnection to have an additional property called FallbackConnection. If the TUniConnection goes offline, the connection attempts to connect the FallbackConnection. If successful, it then sets the Connection properties of all live UniDatasets in the app to the FallbackConnection and re-opens them if necessary. The extended TUniConnection holds a list of datasets that were created. Each dataset is responsible for registering itself with the connection. This is a highly specific feature. It supports an offline mode that is found in mission critical/point of sale solutions. I have never seen it implement before in any DACs, but I think it is a really unique feature with a big impact. Dataset to JSON/XML: A ToSql function on a dataset that creates a full SQL Text statement with all parameters converted to text (excluding blobs) and included in the returned string. Extended TUniScript:- TMyUniScript allows me to add lines of text to a script using the normal dataset functions, Script.Append, Script.FieldByName(‘xxx’).AsString := ‘yyy’, Script.AddToScript and finally Script.Post, then Script.Commit. The AddToScript builds the SQL text statement and appends it to the script using #e above. Record Size Calculation. It would be great if UniDac could estimate the size of a particular record from a query or table. This could be used to automatically set the packet fetch/request count based on the size of the Ethernet packets on the local area network. This I believe would increase performance and reduce network traffic for returning larger datasets. I am aware that this would also be a unique feature to UniDac but would gain a massive performance enhancement. I would suggest setting the packet size on the TUniConnection which would effect all linked datasets.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The ease of usability is the most valuable feature; it's very easy and quick to set up and it also has a central hub as opposed to GoldenGate which is one direct interface, where for GoldenGate I would have needed three interfaces whereas with HVR I have a central interface that manages everything."
"It is not like a traditional ETL, but it gives quite a lot of flexibility."
"The most valuable feature of Fivetran so far is the data replication; the real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline."
"Fivetran can perform data migration incredibly fast, depending on the source and target."
"The simplicity and scalability are the strongest features of Fivetran."
"Making the decision to implement Fivetran was supported by the fact that they have better connectors than other competitors."
"The compare feature is the most valuable piece of it."
"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."
"For what it offers, I think this solution is a must for any Delphi programmer."
 

Cons

"It should have a few more monitoring functionalities."
"The interface needs to be more user-friendly."
"The experience of using SDK connectors can be improved, as it lacks computational power, which is an area that needs enhancement."
"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."
"We use a separate tool for "reverse ETL", which is the opposite of what Fivetran does; it pushes data from your data warehouse back out to business applications. If Fivetran pulls data from those same applications, they should also enable users to push it back. I would love to do both ETL and reverse ETL in the same tool."
"This solution needs to improve its real-time data and transformation availability."
"I would like to see an improvement in the support offered by Fivetran."
"Their pricing has increased over the years, so it's not seen as an advantage anymore."
"Error handling has caused me many problems in the past; when an error occurs, the event on the connection that is called does not seem to behave as documented."
 

Pricing and Cost Advice

"I can't give exact amounts because that's based on usage, but it's more expensive than some of its competitors."
"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."
"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."
"The product is reasonably expensive"
"Fivetran is very expensive, and its database-driven pricing model is outdated."
"I rate the pricing a six out of ten."
"The solution is affordable."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
10%
Computer Software Company
9%
Healthcare Company
6%
Performing Arts
19%
Construction Company
14%
Outsourcing Company
9%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise7
Large Enterprise16
No data available
 

Questions from the Community

What's the deal with the HVR software acquisition?
As a user of HVR Software I followed this deal closely. Fivetran is apparently trying to establish more in its sector and by buying an already established data replication software, they become som...
Does HVR Software provide reliable insights?
I honestly can't think of another data replication software that can give you better statistics and insight than HVR Software. There's the feature for topology and statistics and both of them can ...
How much traffic can HVR Software handle?
As someone who works at a company where a high volume of information is replicated and has tried several data replication softwares, I can tell you that you're looking at the right one. HVR Softwar...
Ask a question
Earn 20 points
 

Comparisons

 

Also Known As

No data available
Skyvia, Skyvia Data Integration
 

Overview

 

Sample Customers

Autodesk, Condé Nast, JetBlue, Morgan Stanley, OpenAI, LVMH, Pfizer, Verizon, SpotifyNational Australia Bank, Saks, Cemex, Okta, Dropbox, Pitney Bowes, World Fuel Services,Lufthansa, AutoZone, ASICS, ASOS, Coupa, Databricks, Hermes, New Relic, Intercom,Canva, Honeywell, Square, DocuSign, Nandos, Oldcastle Infrastructure
Boeing, Sony, Honda, Oracle, BMW, Samsung
Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration. Updated: June 2026.
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