HPE Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform.
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IBM InfoSphere Information Server
Score10 out of 10
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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.
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Pricing
HPE Data Fabric
IBM InfoSphere Information Server
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HPE Data Fabric
IBM InfoSphere Information Server
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Features
HPE Data Fabric
IBM InfoSphere Information Server
Data Source Connection
Comparison of Data Source Connection features of HPE Data Fabric and IBM InfoSphere Information Server
Feature
HPE Data Fabric
-
Ratings
IBM InfoSphere Information Server
8.7
4 Ratings
4% above category average
Connect to traditional data sources
00 Ratings
9.94 Ratings
Connecto to Big Data and NoSQL
00 Ratings
7.54 Ratings
Data Transformations
Comparison of Data Transformations features of HPE Data Fabric and IBM InfoSphere Information Server
Feature
HPE Data Fabric
-
Ratings
IBM InfoSphere Information Server
9.6
4 Ratings
17% above category average
Simple transformations
00 Ratings
10.04 Ratings
Complex transformations
00 Ratings
9.24 Ratings
Data Modeling
Comparison of Data Modeling features of HPE Data Fabric and IBM InfoSphere Information Server
Feature
HPE Data Fabric
-
Ratings
IBM InfoSphere Information Server
8.0
4 Ratings
1% above category average
Data model creation
00 Ratings
8.72 Ratings
Metadata management
00 Ratings
7.74 Ratings
Business rules and workflow
00 Ratings
8.44 Ratings
Collaboration
00 Ratings
8.04 Ratings
Testing and debugging
00 Ratings
7.14 Ratings
Data Governance
Comparison of Data Governance features of HPE Data Fabric and IBM InfoSphere Information Server
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
MapR had very fast I/O throughput. The write speed was several times faster than what we could achieve with the other Hadoop vendors (Cloudera and Hortonworks). This is because MapR does not use HDFS, which is essentially a "meta filesystem". HDFS is built on top of the filesystem provided by the OS. MapR has their filesystem called MapR-FS, which is a true filesystem and accesses the raw disk drives.
The MapR filesystem is very easy to integrate with other Linux filesystems. When working with HDFS from Apache Hadoop, you usually have to use either the HDFS API or various Hadoop/HDFS command line utilities to interact with HDFS. You cannot use command line utilities native to the host operation system, which is usually Linux. At least, it is not easily done without setting up NFS, gateways, etc. With MapR-FS, you can mount the filesystem within Linux and use the standard Unix commands to manipulate files.
The HBase distribution provided by MapR is very similar to the Apache HBase distribution. Cloudera and Hortonworks add GUIs and other various tools on top of their HBase distributions. The MapR HBase distribution is very similar to the Apache distribution, which is nice if you are more accustomed to using Apache HBase.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Increased employee efficiency for sure. Our clients have various levels of expertise in their deployment and user teams, and we never receive complaints about MapR.
MapR is used by one of our financial services clients who uses it for fraud detection and user pattern analysis. They are able to turn around data much faster than they previously had with in-house applications
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info