IBM InfoSphere Information Server vs. Red Hat JBoss Data Virtualization

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM InfoSphere Information Server
Score 8.0 out of 10
N/A
IBM InfoSphere Information Server is a data integration platform used to understand, cleanse, monitor and transform data. The offerings provide massively parallel processing (MPP) capabilities.N/A
JBoss Data Virtualization
Score 6.0 out of 10
N/A
JBoss Data Virtualization is a data integration solution that sits in front of multiple data sources and allows them to be treated as a single source, to deliver the right data, in the required form, at the right time to any application and/or user. Also presented as a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. Red Hat JBoss Data Virtualization makes data spread across physically diverse…N/A
Pricing
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM InfoSphere Information ServerJBoss Data Virtualization
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Features
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM InfoSphere Information Server
8.7
4 Ratings
5% above category average
Red Hat JBoss Data Virtualization
-
Ratings
Connect to traditional data sources9.94 Ratings00 Ratings
Connecto to Big Data and NoSQL7.54 Ratings00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM InfoSphere Information Server
9.6
4 Ratings
16% above category average
Red Hat JBoss Data Virtualization
-
Ratings
Simple transformations10.04 Ratings00 Ratings
Complex transformations9.24 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM InfoSphere Information Server
8.0
4 Ratings
2% above category average
Red Hat JBoss Data Virtualization
-
Ratings
Data model creation8.72 Ratings00 Ratings
Metadata management7.74 Ratings00 Ratings
Business rules and workflow8.44 Ratings00 Ratings
Collaboration8.04 Ratings00 Ratings
Testing and debugging7.14 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
IBM InfoSphere Information Server
9.7
4 Ratings
19% above category average
Red Hat JBoss Data Virtualization
-
Ratings
Integration with data quality tools10.04 Ratings00 Ratings
Integration with MDM tools9.53 Ratings00 Ratings
Best Alternatives
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Small Businesses
Skyvia
Skyvia
Score 10.0 out of 10

No answers on this topic

Medium-sized Companies
dbt
dbt
Score 9.0 out of 10
SAP HANA Cloud
SAP HANA Cloud
Score 8.9 out of 10
Enterprises
InterSystems IRIS
InterSystems IRIS
Score 8.0 out of 10
Perforce Delphix
Perforce Delphix
Score 9.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Likelihood to Recommend
8.9
(5 ratings)
6.0
(2 ratings)
Likelihood to Renew
8.0
(1 ratings)
-
(0 ratings)
Support Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
IBM InfoSphere Information ServerRed Hat JBoss Data Virtualization
Likelihood to Recommend
IBM
Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.
Read full review
Red Hat
Red Hat JBoss Enterprise Data Services is a top choice for JEE applications. Even though lots of documentation is available, it's difficult in terms of usability. If the development is more based on Java applications it is a good choice. It provides better installation and integrations.
Read full review
Pros
IBM
  • IIS best for ETL ,not ELT , and many and diffrent source systems.
  • It also can process big data , unstuctured data
  • It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems
Read full review
Red Hat
  • Data source compatibility: since it is Java, it can connect to anything with a JDBC driver.
  • Flexibility: you can configure it however you want, we have it configured to use LDAPS for authentication and have all interfaces encrypted, and setting that up was pretty straight forward.
Read full review
Cons
IBM
  • I would be nice to have a new web development environment for DataStage.
  • Connectivity Packs such as Pack for SAP Application are a little pricey.
  • It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.
Read full review
Red Hat
  • Pricing
  • User Interface
Read full review
Likelihood to Renew
IBM
  • Scale of implementation
  • IBM techsupport
Read full review
Red Hat
No answers on this topic
Support Rating
IBM
No answers on this topic
Red Hat
Support availability and resolution response time make it a better choice.
Read full review
Alternatives Considered
IBM
DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS
Read full review
Red Hat
Market value and support extended by Redhat is the winner against Veritas. It has cool features and functionality but still, if your organization is Redhat shop it's better to go for the Jboss option.
Read full review
Return on Investment
IBM
  • Productivity of the development of integration processes.
  • Better documentation and governance.
  • Reduce training costs of various technologies.
Read full review
Red Hat
  • It has allowed us to start moving applications independent from their underlying data sources, savings us time and limiting cutover effort.
Read full review
ScreenShots