We performed a comparison between Apache Spark and Pentaho Business Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."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 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."
"This solution provides a clear and convenient syntax for our analytical tasks."
"The solution has been very stable."
"ETL and streaming capabilities."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."
"Spark can handle small to huge data and is suitable for any size of company."
"Pentaho is an analytics platform that can be used when an organization has a lot of big data storage systems already installed and needs to manage and analyze that data. It has a specific use case for unstructured data, such as documents, and needs to be able to search and analyze it."
"Pentaho Business Analytics' best features include the ease of developing data flows and the wide range of options to connect to databases, including those on the cloud."
"Easy to use components to create the job."
"The most valuable feature of Pentaho is the Tableau report."
"The initial setup is pretty straightforward."
"We were able to install it without any assistance from tech support."
"I use the BI Server, CDE Dashboards, Saiku, and Kettle, because these tools are very good and highly experienced."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The logging for the observability platform could be better."
"The solution’s integration with other platforms should be improved."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"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 graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"Another concern is that Pentaho is not customizable or interactive."
"Pentaho, at the general level, should greatly improve the easy construction of its dashboards and easy integration of information from different sources without technical user intervention."
"The repository should be improved."
"We did not achieve the ROI. The work delivered to users had lesser value than the subscription cost."
"Logging capability is needed."
"Version control would be a good addition."
"Pentaho Business Analytics' user interface is outdated."
"Deployment is not simple. It is not simple because we are dealing with a lot of data; we are dealing with a lot of storage. So, it's not a simple process."
Apache Spark is ranked 1st in Hadoop with 60 reviews while Pentaho Business Analytics is ranked 19th in BI (Business Intelligence) Tools with 42 reviews. Apache Spark is rated 8.4, while Pentaho Business Analytics is rated 8.0. 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 Pentaho Business Analytics writes "Flexible, easy to understand, and simple to set up". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Pentaho Business Analytics is most compared with Microsoft Power BI, Databricks, KNIME, SAP Crystal Reports and Microsoft SQL Server Reporting Services.
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