IBM Cloud Pak for Data vs Rivery comparison

IBM and Rivery are both solutions in the Data Integration category. IBM is ranked #23 with an average rating of 7.7, while Rivery is ranked #35 with an average rating of 8.0. IBM holds a 1.3% mindshare in DI, compared to Rivery’s 0.6% mindshare. Additionally, 88% of IBM users are willing to recommend the solution, compared to 100% of Rivery users who would recommend it.

IBM Cloud Pak for Data

Read 15 IBM Cloud Pak for Data reviews

2,163 Views
2,033 Comparison Views

88% willing to recommend

Rivery

Read 4 Rivery reviews

1,027 Views
698 Comparison Views

100% willing to recommend

IBM Cloud Pak for Data

Rivery

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 19, 2024

IBM Cloud Pak for Data and Rivery compete in the data management solutions category. Rivery seems to have the upper hand due to its agility and efficient deployment, appealing to those prioritizing flexibility.

Features: IBM Cloud Pak for Data offers comprehensive integration with AI and machine learning tools, focusing on data governance and security. Rivery provides a no-code interface and strong data pipeline automation, enhancing adaptability through operation simplicity.

Ease of Deployment and Customer Service: IBM Cloud Pak for Data generally requires a more complex setup suitable for detailed customization, backed by a sophisticated customer support framework. Rivery stands out with quick deployment and an intuitive setup, offering proactive customer service.

Pricing and ROI: IBM Cloud Pak for Data may involve higher initial setup costs but targets long-term ROI with deep integration capabilities. Rivery features a simpler pricing model, more affordable initial costs, and offers a higher ROI over shorter periods, making it appealing for budget-conscious businesses.

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

Buyer's Guide

IBM Cloud Pak for Data vs. Rivery

December 2025

Download the complete report

Helped 881,082 peers since 2012

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

IBM Cloud Pak for Data

Ranking in Data Integration

23rd

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Rivery

Ranking in Data Integration

35th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Migration Tools (3rd), Cloud Migration (15th), Cloud Data Integration (19th)

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.3%, down from 1.6% compared to the previous year. The mindshare of Rivery is 0.6%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
IBM Cloud Pak for Data	1.3%
Rivery	0.6%
Other	98.1%

Data Integration

Featured Reviews

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

Doron Matmoni

Manager, Application at a non-profit with 1,001-5,000 employees

Data pipelines have become streamlined and now connect diverse sources with strong support

How Rivery can be improved is a challenging question, but I think something with the graphics could be better because when there is a lot of code inside, it needs to be more user-friendly. I am not talking about the source-to-target, but when we implement a lot of code, you need a different visual of how you use it, such as what you see in DBT. There is a problem where sometimes I run a river and something in the UI does not get refreshed because I think of browser cache limits, which is annoying. I always need to refresh, and then I am not sure, so I have to go inside the river and look in the log to see if it has finished or not, which takes my time. At the end of the day, when I am running the river, I need it to be done before I go to the next step. Something in the UI could work more smoothly to show it easily. I am not sure why it happens, and I am not sure if there is a solution for it, but if it could be more clear, that would be very nice, such as sending an email once the river is really done.

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

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

"IBM Cognos is very stable and has been around for many years, with many users familiar with it, making it a reliable solution for our institution."

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

"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."

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

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

"You can model the data there, connect the data models with the business processes and create data lineage processes."

"IBM Watson Catalog and data pipelines are the most valuable features of the solution."

More IBM Cloud Pak for Data pros

"Rivery has positively impacted my organization by enabling us to create a stable pipeline, and we can expand the variety of the data sources as we go very easily, with no worries, and with a lot of confidence in the fact that it can be done."

"Connects to many APIs in the market and new ones are being added all the time."

"The solution's most valuable features are that it is quick to connect and simple to use."

"Rivery has positively impacted my organization by helping me streamline my data ingestion and transformation processes, especially in combination with Snowflake."

Cons

"The solution's user experience is an area that has room for improvement."

"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."

"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 two main challenges that I face are setup complexity and customer support responsiveness."

"The solution's catalog searching or map search needs to be improved."

"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."

"The technical support could be a little better."

"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."

More IBM Cloud Pak for Data cons

"Lineage and an impact analysis or logic dependency are lacking."

"My experience with pricing, setup cost, and licensing was unfortunately not so good in my recent data project."

"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."

Pricing and Cost Advice

"The solution is expensive."

"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."

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

"It's quite expensive."

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

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

"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."

"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 rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

881,082 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

26%

Manufacturing Company

10%

Computer Software Company

Government

Manufacturing Company

11%

Comms Service Provider

10%

Computer Software Company

10%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	7
Large Enterprise	12

No data available

Questions from the Community

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

The pricing and setup cost are handled by a different procurement team. Our IT procurement team is centralized, so licensing and the actual cost of the software are taken care of by a different tea...

See all answers

What needs improvement with IBM Cloud Pak for Data?

I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.

See all answers

What is your primary use case for IBM Cloud Pak for Data?

The main use case for IBM Cognos is for business intelligence and reporting.

See all answers

What is your experience regarding pricing and costs for Rivery?

The tool's price can be a little steep for a small organization. I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten.

See all answers

What needs improvement with Rivery?

I don't know what could be improved in terms of what my company was used to previously or after moving over to Rivery. I have not had much experience with platforms other than Rivery. For me, Rival...

See all answers

What is your primary use case for Rivery?

My company has started to use the Rivery extract data from Hive. It is like a project management sort of program, and we started to use Rivery to get the data from there over into Mavenlink, so we ...

See all answers

Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 39% of the time

Denodo vs IBM Cloud Pak for Data

Compared 12% of the time

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

Compared 8% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 7% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 6% of the time

More IBM Cloud Pak for Data Competitors

dbt vs Rivery

Compared 17% of the time

Matillion Data Productivity Cloud vs Rivery

Compared 17% of the time

Azure Data Factory vs Rivery

Compared 16% of the time

OpenText Migrate vs Rivery

Compared 9% of the time

AWS Glue vs Rivery

Compared 8% of the time

More Rivery Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

January 2026

Download IBM Cloud Pak for Data product report

Buyer's Guide

Data Integration

January 2026

Download Rivery product report

Also Known As

Cloud Pak for Data

No data available

Overview

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

Rivery is a serverless, SaaS DataOps platform that empowers companies of all sizes around the world to consolidate, orchestrate, and manage internal and external data sources with ease and efficiency.

By offering comprehensive data solutions and partnering with complementary technology providers, including Google, Snowflake, Tableau, and Looker, Rivery enables data-driven companies to build the perfect ecosystems for all their data processes.

Rivery

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Information Not Available

Buyer's Guide

IBM Cloud Pak for Data vs. Rivery

December 2025

Free Report: IBM Cloud Pak for Data vs. Rivery

Find out what your peers are saying about IBM Cloud Pak for Data vs. Rivery and other solutions. Updated: December 2025.

DOWNLOAD NOW

881,082 professionals have used our research since 2012.

See our IBM Cloud Pak for Data vs. Rivery report.

See our list of best Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.