We performed a comparison between IBM InfoSphere BigInsights [EOL] and Spark SQL 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."
"Certain data sets that are very large are very difficult to process with Pandas and Python libraries. Spark SQL has helped us a lot with that."
"It is a stable solution."
"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."
"Data validation and ease of use are the most valuable features."
"The performance is one of the most important features. It has an API to process the data in a functional manner."
"This solution is useful to leverage within a distributed ecosystem."
"The UI was not interactive: Responses used to be very slow and hang up at times."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper."
"Anything to improve the GUI would be helpful."
"Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users."
"In the next release, maybe the visualization of some command-line features could be added."
"SparkUI could have more advanced versions of the performance and the queries and all."
"I've experienced some incompatibilities when using the Delta Lake format."
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IBM InfoSphere BigInsights [EOL] doesn't meet the minimum requirements to be ranked in Hadoop while Spark SQL is ranked 4th in Hadoop with 14 reviews. IBM InfoSphere BigInsights [EOL] is rated 7.6, while Spark SQL 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 Spark SQL writes "Offers the flexibility to handle large-scale data processing". IBM InfoSphere BigInsights [EOL] is most compared with , whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, SAP HANA, HPE Ezmeral Data Fabric and Netezza Analytics.
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