Fivetran vs IBM Cloud Pak for Data comparison

Fivetran and IBM are both solutions in the Data Integration category. Fivetran is ranked #12 with an average rating of 7.9, while IBM is ranked #24 with an average rating of 8.0. Fivetran holds a 2.3% mindshare in DI, compared to IBM’s 2.0% mindshare. Additionally, 89% of Fivetran users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Fivetran

Read 27 Fivetran reviews

2,733 Views
1,664 Comparison Views

89% willing to recommend

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,349 Views
1,342 Comparison Views

86% willing to recommend

Fivetran

IBM Cloud Pak for Data

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

IBM Cloud Pak for Data and Fivetran compete in the data integration and management space. IBM Cloud Pak for Data has the advantage in terms of support and pricing satisfaction, while Fivetran stands out with its robust features that justify its cost.

Features: IBM Cloud Pak for Data integrates diverse data sources, providing a unified platform for AI-driven insights. It offers advanced analytics capabilities and strong governance features. In contrast, Fivetran is known for its seamless data pipeline automation and efficient data connectors, simplifying the ETL process. Its automation and simplicity significantly differentiate it from competitors.

Room for Improvement: IBM Cloud Pak for Data could enhance its deployment simplicity and reduce its complexity for businesses with limited IT resources. Its customer service could benefit from more streamlined processes. Fivetran might improve in providing more personalized support and enhancing its flexibility for complex data processes. The cost structure could be more adaptive to different scales of data usage.

Ease of Deployment and Customer Service: IBM Cloud Pak for Data requires a comprehensive setup and a detailed deployment strategy, which can be complex. It features a notably hands-on customer service providing in-depth assistance. Fivetran, contrastingly, offers a straightforward deployment with plug-and-play functionality, focusing on ease and efficiency. Its customer service is efficient but more tailored to automated processes rather than personalized support.

Pricing and ROI: IBM Cloud Pak for Data typically involves a more substantial initial investment but delivers strong long-term ROI through extensive capabilities and scalable infrastructure. Fivetran, with a lower upfront cost, provides attractive quick return benefits due to its efficient data handling, but its ROI is highly dependent on the volume and complexity of data processes, potentially making it a more costly solution over time.

To learn more, read our detailed Fivetran vs. IBM Cloud Pak for Data Report (Updated: June 2025).

Buyer's Guide

Fivetran vs. IBM Cloud Pak for Data

June 2025

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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

12th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Replication (3rd), Cloud Data Integration (6th)

IBM Cloud Pak for Data

Ranking in Data Integration

24th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Mindshare comparison

As of July 2025, in the Data Integration category, the mindshare of Fivetran is 2.3%, up from 2.0% compared to the previous year. The mindshare of IBM Cloud Pak for Data is 2.0%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Mediha Šiljić

Lead Data Engineer at Sensilab

Built-in connectors offer extensive data source integration and time savings

Fivetran could improve by adapting more for technical users and by providing more options for such users. There should be more adaptability in terms of new features. If a specific feature is required, it should be integrated promptly. Improvement in existing connectors with new features is desirable. Enhancements around customer-focused product adaptation are also suggested.

Read full review

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

Read full review

Quotes from Members

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

Pros

"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 ease of usability is the most valuable feature. It's very easy and quick to set up. It also has a central hub as opposed to GoldenGate which is one direct interface. For GoldenGate I would have needed three interfaces whereas with HVR I have a central interface that manages everything."

"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,."

"It is not like a traditional ETL, but it gives quite a lot of flexibility."

"The simplicity and scalability are the strongest features of Fivetran."

"The most important feature of the solution is its ability to build data pipelines in less time."

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

"Fivetran's most valuable feature is replication."

More Fivetran pros

"Its data preparation capabilities are highly valuable."

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

"Cloud Pak is a very, very, very good system."

"Scalability-wise, I rate the solution a nine or ten out of ten."

"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."

"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."

"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

More IBM Cloud Pak for Data pros

Cons

"An in-line data quality checking capability is missing"

"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 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."

"Fivetran would be improved by adding the ability to integrate the data from third-party APIs."

"I would like Fivetran to implement additional resource monitoring and restriction policies."

"The biggest area for improvement is in customization, particularly in how Fivetran socializes its tools."

"Their pricing has increased over the years, so it's not seen as an advantage anymore."

"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."

More Fivetran cons

"What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated."

"The technical support could be a little better."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"The product must improve its performance."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"Cloud Pak would be improved with integration with cloud service providers like Cloudera."

"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."

"The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem."

More IBM Cloud Pak for Data cons

Pricing and Cost Advice

"When you have a lot of workflows and complex use cases, pricing goes down as you use it more."

"I rate the pricing a six out of ten."

"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."

"The solution is affordable."

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

"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."

"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 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."

More Fivetran pricing and cost advice

"The solution's pricing is competitive with that of other vendors."

"The solution is expensive."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"It's quite expensive."

"I think that this product is too expensive for smaller companies."

"Cloud Pak's cost is a little high."

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

13%

Educational Organization

10%

Manufacturing Company

10%

Financial Services Firm

30%

Computer Software Company

10%

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

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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 ...

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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...

See all answers

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

See all answers

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

See all answers

What needs improvement with IBM Cloud Pak for Data?

See all answers

Comparisons

AWS Database Migration Service vs Fivetran

Compared 14% of the time

Oracle GoldenGate vs Fivetran

Compared 12% of the time

Qlik Replicate vs Fivetran

Compared 8% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Fivetran

Compared 6% of the time

AWS Glue vs Fivetran

Compared 5% of the time

More Fivetran Competitors

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 40% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 13% of the time

Denodo vs IBM Cloud Pak for Data

Compared 12% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 10% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 9% of the time

More IBM Cloud Pak for Data Competitors

Product Reports

Buyer's Guide

Fivetran

June 2025

Download Fivetran product report

Buyer's Guide

IBM Cloud Pak for Data

June 2025

Download IBM Cloud Pak for Data product report

Also Known As

No data available

Cloud Pak for Data

Overview

Fivetran, the global leader in data movement, is trusted by companies like OpenAI, LVMH, Pfizer, Verizon and Spotify to centralize data from SaaS applications, databases, files, and other sources into cloud destinations, including data lakes. With high-performance pipelines, seamless interoperability, and enterprise-grade security, Fivetran empowers organizations to modernize their data infrastructure, power analytics and AI, ensure compliance, and achieve transformative business outcomes. Learn more at Fivetran.com

Fivetran

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

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

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Buyer's Guide

Fivetran vs. IBM Cloud Pak for Data

June 2025

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