We performed a comparison between IBM InfoSphere BigInsights [EOL] and IBM Spectrum Computing based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."InfoSphere Streams was the one core product from the platform in which we were using. We were building a real-time response system and we built it on InfoSphere Streams."
"Spectrum Computing's best features are its speed, robustness, and data processing and analysis."
"The most valuable feature is the backup capability."
"The most valuable aspect of the product is the policy driving resource management, to optimize the computing across data centers."
"This solution is working for both VTL and tape."
"Easy to operate and use."
"We are satisfied with the technical support, we have no issues."
"The UI was not interactive: Responses used to be very slow and hang up at times."
"We have not been able to use deduplication."
"We'd like to see some AI model training for machine learning."
"Lack of sufficient documentation, particularly in Spanish."
"This solution is no longer managing tapes correctly."
"Spectrum Computing is lagging behind other products, most likely because it hasn't been shifted to the cloud."
"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
Earn 20 points
IBM InfoSphere BigInsights [EOL] doesn't meet the minimum requirements to be ranked in Hadoop while IBM Spectrum Computing is ranked 7th in Hadoop with 6 reviews. IBM InfoSphere BigInsights [EOL] is rated 7.6, while IBM Spectrum Computing is rated 7.8. The top reviewer of IBM InfoSphere BigInsights [EOL] writes "The BIQSQL implementation is fully SQL ANSI compliant, but I have found a lot of issues in Fluid Query". On the other hand, the top reviewer of IBM Spectrum Computing writes "Provides stable backup for our databases and has good technical support ". IBM InfoSphere BigInsights [EOL] is most compared with , whereas IBM Spectrum Computing is most compared with Apache Spark, HPE Ezmeral Data Fabric and IBM Turbonomic.
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