We performed a comparison between Apache Spark and IBM InfoSphere BigInsights [EOL] based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."The processing time is very much improved over the data warehouse solution that we were using."
"The product's deployment phase is easy."
"Features include machine learning, real time streaming, and data processing."
"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."
"The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"Spark can handle small to huge data and is suitable for any size of company."
"I found the solution stable. We haven't had any problems with it."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"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."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"They could improve the issues related to programming language for the platform."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"It should support more programming languages."
"The UI was not interactive: Responses used to be very slow and hang up at times."
Earn 20 points
Apache Spark is ranked 1st in Hadoop with 60 reviews while IBM InfoSphere BigInsights [EOL] doesn't meet the minimum requirements to be ranked in Hadoop. Apache Spark is rated 8.4, while IBM InfoSphere BigInsights [EOL] is rated 7.6. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, 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". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas IBM InfoSphere BigInsights [EOL] is most compared with .
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