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AWS Data Pipeline [EOL] vs Skyvia comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Nov 23, 2025

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

AWS Data Pipeline [EOL]
Average Rating
8.0
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Skyvia
Average Rating
9.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
Data Integration (62nd), Cloud Data Integration (29th)
 

Featured Reviews

BR
Senior Director Data Architecture at Managed Markets Insight & Technology, LLC
A tool with great orchestration and development capabilities but needs to improve its user-defined functions
In the tool, parallel processing is an area that is contingent, in the sense that you have to be watchful for the cap that you have in terms of computing behind AWS Data Pipeline. You need to always watch for some reason. I am capped with 200 nodes, and if I get to use more than 200 nodes, the AWS Data Pipeline will fail. AWS doesn't state that I have almost gone beyond my limits, and it is allowing me now to go beyond the set limits if I talk to a representative and figure it out. Such aforementioned warnings are not let out by AWS, and they end up failing the nodes if I go beyond the set cap limits.
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 most valuable feature of the solution is that orchestration and development capabilities are easier with the tool."
"It is a stable solution...It is a scalable solution."
"For what it offers, I think this solution is a must for any Delphi programmer."
 

Cons

"It's almost semi-automatic because you must review and approve code push, which works well. Still, we had many problems getting there during the deployment process, but we got there."
"The user-defined functions have shortcomings in AWS Data Pipeline."
"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 rate the pricing between six to eight on a scale from one to ten, where one is low price, and ten is high price."
"The way we use it, I think it is fair as we're getting a good value for money compared to having a server or some other data pipeline."
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Top Industries

By visitors reading reviews
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Construction Company
15%
Performing Arts
15%
Outsourcing Company
10%
Comms Service Provider
8%
 

Company Size

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Large Enterprise
Midsize Enterprise
Small Business
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Also Known As

No data available
Skyvia, Skyvia Data Integration
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
Boeing, Sony, Honda, Oracle, BMW, Samsung
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