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."Features include machine learning, real time streaming, and data processing."
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"The product's deployment phase is easy."
"The product’s most valuable features are lazy evaluation and workload distribution."
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"The main feature that we find valuable is that it is very fast."
"The solution has been very stable."
"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."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"It should support more programming languages."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"The logging for the observability platform could be better."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"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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